Linguistic Principles of C2 Languages and Grammars

10S-SIW-017

Linguistic Principles of C2 Languages and Grammars Dr. Ulrich Schade Fraunhofer FKIE Neuenahrer Str. 20 Wachtberg, 53343 Germany 0049-228-9435-376 [email protected]

Dr. Michael R. Hieb Center of Excellence for C4I George Mason University 4400 University Drive Fairfax, VA 22030 USA 001-703-993-3990 [email protected]

Keywords: Grammar, Linguistics, Orders, Command and Control Lexical Grammar (C2LG), Battle Management Language (BML) ABSTRACT: The specification of a language always is based on a grammar. This is especially true if the language is used for inter-system communication: Automated systems demand the foundation of the language on a formal grammar. During past decade, a precise language for C2, Battle Management Language (BML), has been under development as a standard for assigning C2 tasks to units in simulation system. In this paper, we refer to a BML implementation developed for use by the NATO Technical Activity MSG-048. With respect to grammar, there have been arguments for a regular grammar as a basis for a formal C2 language. We will show that regular grammars are not appropriate for this. We will also discuss the requirements for grammars that are the basis for military communication between C2 systems as well as between C2 systems and simulation systems. These requirements are fulfilled by the Command and Control Lexical Grammar (C2LG) which is a context-free grammar. C2LG defines the linguistic basis for “Coalition Battle Management Language” used in the NATO RTO MSG 048 activity.

10S-SIW-017 Page 2 of 11

1

Introduction and Structure of the Paper

Formally, languages are defined by grammars: According to such a formal linguistic approach, a language is the set of all the sentences that can be generated by its grammar. The language we want to define is a language for Command and Control. This C2 language (implemented as “Battle Management Language”) is supposed to be an “unambiguous language used to command and control forces and equipment conducting military operations and to provide for situational awareness and a shared, common operational picture” [4]. Our conception of a formal C2 language and its theoretical background have already been discussed in detail [1, 4, 24]; versions have been implemented and successfully tested in demonstrations and in experiments, e.g. by NATO MSG-048 “Coalition BML” [2, 6, 7, 14, 15, 16, 17]. The version implemented by MSG048 also has been based on a formal grammar, the context-free Command and Control Lexical Grammar (C2LG). C2LG has been proposed by the authors in former SIW papers [18, 19]. However, although C2LG has been successfully tested, it has been questioned. In particular, [23] rejected the idea that the formal grammar upon which a C2 language had to be based, must be context-free. In contrast, those authors have recommended using a “regular” grammar as a foundation for a MSG-048 BML implementation. As SISO now approaches an initial standardization of a BML implementation– which, of course, will have to include the determination of its grammar type – this paper has been written to discuss the requirements a C2 language grammar needs to fulfil. In addition, we will prove in this paper that only a context-free grammar can fulfil these requirements.

The paper is structured as follows. First, we will present an overview over the types of formal grammars. This will include all necessary definitions (section 2.1) as well as a clarification as to how formal grammars are related to automatons (section 2.2). Then, we will discuss the requirements for C2 communications in general and for a C2 language in particular (section 3). In section 4, we will show that in order to fulfil the requirements, the formal grammar for a C2 language must be a contextfree grammar. We will even go somewhat further and will show what additional constraints should be laid upon a C2 language grammar: We will argue in favour of the use of a “lexical” context-free grammar. As a conclusion, we will discuss how our C2 language approach, a C2 language based upon a lexical context-free grammar, differs from other approaches to exchange C2 data, C2 information, and C2 messages.

2

Formal grammars

It is necessary to have a formal grammar to define a C2 language because the language has to be processed by systems. Formal grammars have been introduced into the field of linguistics by Noam Chomsky. In “Syntactic Structures” [5], published in 1957, Chomsky answered the question “What do we know when we know a language?” by postulating that what we know is a set of words (the lexicon of that language) and a set of production rules that can be used to generate sequences of those words, especially the language’s sentences. In principle, a sequence of words is called well-formed or “grammatical” if the sequence can be generated by the production rules operating on the lexicon. One of Chomsky’s key insights had been that grammaticality is independent from meaning. Chomsky gave the example (1) of a


grammatical but not meaningful sequence in order to illustrate this point. In addition, word sequence can be meaningful although they are not grammatical as is shown by example (2). (1) (2)

Colorless green ideas sleep furiously. The unit to the phase advances.

Following Chomsky’s approach, a formal grammar G is a quadruple, G = (S, N, , P), where S is the starting symbol, N is a finite set of non-terminal symbols,  is a finite set of terminal symbols (the lexicon), and P is a finite set of production rules. A production rule expands a sequence of symbols taken from the union of N and  to another sequence of symbols taken from the union of N and . The only restriction is that the left-hand side of a rule must contain at least one non-terminal symbol. The language generated by G, L(G), is the set of all sequences of symbols from  which can be produced by applying the rules of P, starting from S. Although N, , and P are finite sets, L(G) need not be finite because recursion is allowed.

2.1 Types of Formal Grammars The definition of a formal grammar as given above is quite abstract. It allows the construction of different types of formal grammars by applying restrictions to production rules. Linguistic theory categorizes the set of formal grammars into four types that form the Chomsky hierarchy [5; 13, section 16.5]: grammars of type 0 (unrestricted grammars), grammars of type 1 (context-sensitive grammars), grammars of type 2 (context-free grammars), and grammars of type 3 (regular grammars). The type of production rules which are used in the definition of a specific formal grammar define the type of that grammar. Only grammars of types 2 and 3 exclusively use rules that can easily be applied by automated systems.

Thus, only these kinds of grammars can easily be automatically processed. Therefore, our formal language should have a grammar of type 2 or 3. In linguistics, there has been a detailed discussion as to whether grammars of type 2 (context-free grammars) are sufficient to describe natural language like English, cf. [13, section 18.6]. The result of the discussion was that it is quite probable that context-free grammars are not sufficient and a grammar of type 1 (a context-sensitive grammar) might be needed. However, it was clear that nearly all constructions in all natural languages can be “elegantly and efficiently” processed by context-free techniques [8, p. 133]. As the C2 language does not need such exceptional constructions – on the contrary, these constructions would endanger our requirement that C2 language has to be unambiguous – it is sufficient to restrict the search for a C2 language grammar to context-free and regular grammars. That, of course, is good news because, as already, mentioned, grammars of that types can easily be automatically processed. So, what is the difference between a grammar of type 2 (a context-free grammar) and a grammar of type 3, (a regular one)? Grammars of type 3 (regular grammars) only allow two types of rules “A → a” and “A → aB”. In these rules, “a” represents a terminal symbol (a word) and “A” and “B” represent non-terminal symbols. In contrast, grammars of type 2 use rules that allow the expansion of a non-terminal by any sequence of terminals and non-terminals. Thus, type 2 grammars have rules of the form “A → ” in which  represents such a sequence. As in type 3 grammars, the left side of every rule consists of exactly one non-terminal symbol. In order to illustrate the consequences that lie behind the differences between regular and context-free grammars, we now will take a look at an example: We will discuss grammars that can generate the sequence “advance to


X1 → phase_line X2, X2 → alpha StartWhen, StartWhen → begin X3, X3 → ntl TimePointName, TimePointName → date_time_0}). This regular grammar generates a language that only has one sentence, namely the example sequence. The structure Figure 1: The structure assigned to the sequence “advance to that is assigned to the example sequence by the phase_line alpha begin nlt date_time_0” by a regular grammar. regular grammar is a phase_line alpha begin nlt date_time_0”. To do right-linear one as given in figure 1. so, we always need a lexicon that includes the words of that sequence. Thus, we have  = Since context-free grammars are less restricted {advance, to, phase_line, alpha, begin, nlt, by how their production rules have to look, date_time_0}. First, we will construct the there are many possibilities to construct a regular grammar that generates the example context-free grammar that generates a language sequence. Since a regular grammar has only two that consists of exactly the example sequence. In types of rules and since one of these rules only particular, since every regular grammar also is a maps a non-terminal symbol on a word (= context-free grammar, the grammar terminal symbol), we only have one type of rule Grammar_regular is also an example of a that we can use to build up a sequence of words: context-free grammar that generates this “A → aB”. This rule type only allows very sequence. Another quite simple grammar that specific kind of rules, namely rules that detach does the job is Grammar_context_free_simple: exactly one word from a sequence. In principle, the rule form of a regular grammar is the rule Grammar_ context_free_simple = (S, N_cfs, , for the construction of lists in LISP or P_cfs) = (S, {S}, {advance, to, phase_line, PROLOG, List = [Head|RestList] whereas a rule alpha, begin, nlt, date_time_0}, {S → advance of a regular grammar has to use one specific to phase_line alpha begin nlt date_time_0}). atom instead of the variable “Head”. This means that the regular rules to generate the example The grammar Grammar_context_free_simple sequence are the following ones: P_regular = {S simply maps the starting symbol S to the → advance X0, X0 → to X1, X1 → phase_line example sequence. The structure that is assigned X2, X2 → alpha StartWhen, StartWhen → to the sequence in this case is shown in figure 2. begin X3, X3 → ntl X4, TimePointName → date_time_0}. In sum, the regular grammar that Looking at the example sequence, it is obvious that the sequence can “naturally” split into three generate the example sequence is parts: “advance”, “to phase_line alpha,” and Grammar_regular = (S, N_regular, , P_regular) “begin nlt date_time_0”. In the terms of the = (S, {S, X0, X1, X2, X3, X4, StartWhen}, 5Ws (Who, What, Where, When, Why), these {advance, to, phase_line, alpha, begin, nlt, parts correspond to What, Where, and When, date_time_0}, {S → advance X0, X0 → to X1, respectively. A context-free grammar that


respects that partition Grammar_context_free_5W.

is

Grammar_ context_free_5W = (S, N_cf5W, , P_cf5W) = (S, {S, What, Where, When, WhereQualifier, FacilityType, FacilityName, WhenQualifier, TimePointName}, {advance, to, phase_line, alpha, begin, nlt, date_time_0}, {S → What Where When, What → advance, Where → WhereQualifier FacilityType FacilityName, WhereQualifier → to, FacilityType → phase_line, FacilityName → alpha, When → begin WhenQualifier TimePointName, WhenQualifier → nlt, TimePointName → date_time_0}). The structure that is assigned to the example sequence by Grammar_context_free_5W is shown in figure 3.

2.2

Grammars and Automata

Formal grammars tell us how sequences of words are generated from a lexicon by production rules. The major task in language processing, however, is not generating but parsing. Parsing means recognizing a string that is a sequence of words, and assigning a syntactic structure to that sequence [10, chapter 3]. The process of parsing can be described with

automata. “An automaton is an idealized abstract computing machine” [13, p. 453]. In the case of parsing, the automaton begins in its starting state and then goes from one state to another. The transitions are triggered by an input, e.g., taking the next word from the sequence. As an output, the automaton changes the structure to assign to the sequence. If the automaton can process the whole sequence and finishes in a pre-defined end state, the structure it has built up during the process is the sequence’s structure. Automata also form a hierarchy. The hierarchy for automata corresponds to Chomsky’s hierarchy for grammars. More precisely, regular grammars correspond to finite state automata and context-free grammars to pushdown automata [13, chapter 17 and chapter 18, respectively]. A pushdown automaton is a finite automaton with “an auxiliary tape on which it may read, write, and erase symbols” [13, p. 487]. In other words, a pushdown automaton is a finite automaton with memory. In [23], it is argued that the grammar of a BML implementation has to be a regular one such that it can be run on finite automata. However, since pushdown automata are finite automata with memory and since most real-life computers do have some memory, the use of a context-free grammar for BML implementation does not hinder the processing of BML expressions on computers.

Figure 3: The structure assigned to the sequence “advance to phase_line alpha begin nlt date_time_0” by a context-free grammar inspired by the 5W paradigm.


3 Grammar Communication

Requirements

for

C2

In this section, we will argue that expressing C2 communications, in particular orders and reports, in a formal language to allow automatic processing should take into account that C2 communication follows doctrine. In particular, doctrinal requirements should be noticeable in the formal structure that is assigned to expressions by a formal grammar. For orders, the documents that determine the doctrine behind them include NATO’s STANG 2014 “Formats for Orders and Designation of Timings, Locations and Boundaries” and the US Army’s Field Manual 6-0 “Mission Command: Command and Control of Army Forces”. In particular, these documents describe the operation order, or “five paragraph field order”. The core of the operation order is paragraph 3 “Execution” in which tasks are assigned to units. The assignment of the tasks to units is also the core information that has to be delivered to a simulation system in order to allow that system to simulate the execution of the order received. We will therefore focus our discussion in this paper on how to express task assignments. For information on how to represent other information included in an order in C2LG, cf. [9] which focuses on how to represent the command intent. An even broader perspective is given in [20] which discusses the grammar’s application to multi-agency communication and coordination.

3.1 The 5Ws, Syntactic Constituents, and Thematic Roles With respect to task assignment, doctrine refers to the 5Ws, the What (what kind of task is to be executed), the Who (the unit that is ordered to execute the task), the Where (the spatial

conditions of the task), the When (the temporal conditions of the task), and the Why (the task’s purpose which links it to the concept of operations). A task assignment in C2LG includes all these aspects but adds some more to ensure the required unambiguousness of the expression. The general rule form of C2LG for task assignments is given in (3) whereas (4) shows an example expression which following this rule. For more details and examples, cf. [18]. (3) TaskAssignment  TaskVerb TaskerWho TaskeeWho (Affected) Where When Modifier Why Label (4)

occupy BN-661 Coy2 Prins Willem-Alexander Brug at Parnass start at TP1 in-manner fast in-order-to enable label-o24 label-o23;

A C2LG expression that assigns a task to a unit starts with the tasking verb which denotes the task. This is the What of the 5Ws. In example (4) the tasking verb is “occupy”. Next come Tasker and Taskee, the Whos. In (4) the Tasker is battalion 661, and the Taskee is its 2nd company. The “Affected” of the task is whatever is affected by the task. In the example it is the Prins Willem-Alexander Brug (Prince Willem Alexander bridge). “At Parnass” is the denotation of a location, the Where; “start at TP1” is the When, “in-manner fast” a Modifier, and “in-order-to enable label-o24” is a Why. “Label-o24” refers to another task assigned to the same company, namely to secure the bridge. All C2LG expressions end with a label such that they can be referred to by other expressions. The label in (4) is “label-o23”. Linguistic theory uses the concept of “constituency” to refer to the idea that some words in an expression belong together because as a whole, they denote a real world object, an idea, a spatial object, a temporal object or something similar. Constituents are the building blocks of sentences. They are the linguist


version of the 5Ws. Cf. [21, section 2] or [10, section 12.1] for more details on constituency. Whenever a language expression is to be analyzed, thematic roles [22] are assigned to constituents, determining the constituents’ roles in the expression. For example, in (4), the Where constituent “at Parnass” needs to be assigned the thematic role “location”. Analyzing C2LG expressions follows this line. The simulation system receiving the expression should receive a representation of the expression in which roles are assigned to the constituents and where the constituents are reduced to terms that can be interpreted by the simulation system. In the MSG-048 demonstrations, BML expressions are transformed to XML representations in which thematic roles serve as attributes and C2LG words serve as values. The C2LG words are values from the JC3IEDM. Thus they are well-defined in agreement with doctrine. Even more importantly, building the C2LG lexicon on JC3IEDM allows to map C2LG expressions on corresponding JC3IEDM representations. 3.2 Lexicality and Other Linguistic Principles C2LG considers even stricter principles than applying constituency on the basis of the 5Ws. It is lexically driven. This lexicality is most obvious with respect to task assignment expressions. The central lexical element for any of these expressions is the verb that denotes the task. In C2LG, there is exactly one rule form for task assignments, the one given in (3). This rule form is not a rule in itself. Instead, there many such rules; one rule for each tasking verb. Each of these lexical rules includes restrictions that are specific for that task and thus collectively cannot be captured by one single rule for all task assignments. For example, the rule for the “advance” task does not include an “Affected”. In addition, its Where has to denote a route: it has to be a “RouteWhere”. In contrast, the rule for occupy (cf. (4) for an expression built according to that rule) includes an “Affected”,

which must be of type “facility”, and its Where has to denote a location, i.e., it must be an AtWhere. Since C2LG respects lexicality, it is a lexical grammar as indicated by the “L”. To be more precise, C2LG has been modeled on Lexical Functional Grammar (LFG) [3, 11]. C2LG has also applied the linguistic principles of coherence and completeness following LFG [3, section 4.7] in this aspect. The principle of completeness says that if a tasking verb mandatorily licenses a thematic role, an expression using that verb must have a constituent that takes that role. For example, the tasking verb “advance” licenses the mandatory role Destination, a sub-role of Where, thus an expression assigning an advance task must express the destination of that movement in order to be grammatical. Another example is “ambush” which licenses the mandatory role Affected (of type unit), ergo an ambush task assignment must express who is to be ambushed. The principle of coherence is the other way around: it states that any constituent that occurs must not be prohibited by the respective tasking verb. For example, the task “rest” licenses the mandatory role Location, which means that those spatial roles denoting the spatial conditions of a movement are prohibited. Thus, the principle of coherence says that an expression that assigns a “rest” may not have a destination, an origin, or a path constituent.

3.3 Adequate Grammar Type for C2 Grammars In this section, we will argue that, in contrast to the context-free grammar C2LG which we presented and discussed above, regular grammars cannot assign adequate structures, i.e., structures consistent with doctrine, to expressions. It is well documented that regular grammars are not adequate to define a natural language, cf. [5;


13, section 17.3.2: “Inadequacy of right-linear grammars for natural languages”; 10, section 12.6]. However, as the arguments presented by Partee, ter Meulen and Wall concern embedded recursion, they do not hold for our purposes, since embedded recursion is not a property needed in a C2 language. Thus, a regular grammar can generate a C2 language. Nevertheless, a regular grammar is not adequate, although the contrary has been asserted in [23]. The reason for this is that a regular grammar does not assign appropriate structures to the expressions. This fact can best be explained by taking a look at the approach that [23] proposes for the development of a BML implementation based on a regular grammar [23, section 2.2]. This approach consists of three steps. In the first step, all expressions that need to be part of that BML implementation are enumerated. Next, a regular grammar is constructed to generate those expressions: “In the second phase, a generative regular grammar is used to replace the enumeration with rules on how to construct valid expression by combinations of Composites/ICEs.” The “composites” or “Information Content Elements (ICE)” are the JC3IEDM’s equivalents to the constituents of linguistic theory. An example of such a composite is the composition of a temporal qualifier and its corresponding datetime as a “When”. In contrast to what [23] postulates for their second step of BML construction, combinations of such composites or constituents cannot be constructed by a regular grammar because, by definition, a regular grammar is right-linear, cf. section 2.1, cf. figure 1. Rightlinear means that one has to add one primitive element (terminal element) of an expression after the other until the whole expression is finished. It is not possible to first combine primitive elements together – which would be needed in order to construct constituents/composites/ICEs that represent the 5Ws – and then afterwards form the expression by combining the composites. So, under the use

of a regular grammar, the second step in Tolk et al.’s approach must fail. If, in their approach, the regular grammar is replaced by a contextfree one, e.g., the C2LG, the approach can be used [12]. Constituents are the building blocks of expressions whether they are called “W”, “composite” or “ICE”. An appropriate contextfree grammar assigns a structure to a language expression that unambiguously identifies the constituents as such and labels them with their roles. C2LG goes one step further. According to its rules, the sequence of constituents in the expressions is fixed. Additionally, most of the constituents start with a specific keyword, e.g., the Why starts with the keyword “in-order-to”. Due to these two restrictions, the thematic role of each constituent of a C2LG expression can be unambiguously determined. This allows the unambiguous transformation of the expressions into an XML representation which has the roles as attributes. For MSG-048, this XML is defined by a specific BML schema. The XML representation can be exchanged between systems by web services such as MSG-048’s Scripted BML WS [16, section 4.6] and unambiguously interpreted by the receiving system, e.g., a simulation system.

4

Relationship to JC3IEDM

The primary standard for exchanging C2 data and information is the JC3IEDM developed by the MIP. MIP has made the JC3IEDM public with the intention that people would build applications which are compatible with it. The BML implementation used by MSG-048 is such an application: as has been shown in many demonstrations and experiments, e.g., those performed by the NATO MSG-048 BML allows sending orders to and receiving reports from simulation systems. Furthermore, all the data communicated in these orders and reports are stored in the underlying JC3IEDM database. It


is also possible to use a formal C2 language for C2 communication. The representation of orders in the JC3IEDM still allows free-text entries not connected to the data stored elsewhere in the database. The substitution of the free-text entries through the MSG-048 BML expressions would make those missing connections by using MSG-048’s mapping application from MSG048 BML expressions to JC3IEDM data entries. This connection between a C2 language and the JC3IEDM is not coincidence. It results from the decision to use JC3IEDM terms as the MSG048 BML’s implementation lexical items: As previously mentioned, the set of C2LG terminal symbols – its lexicon  – is taken from JC3IEDM’s attribute values. This allows the mapping from MSG-048 BML expressions to JC3IEDM data entries. However, it is not the case that the structure of the JC3IEDM is always mirrored by C2LG. JC3IEDM’s structure is, of course, optimized with respect to database demands. The structure is a database’s structure. In contrast, the structure that is assigned to C2 language expressions by C2LG’s production rules is a syntactic structure, optimized according to linguistic principles. Often these two structures go hand in hand but sometimes differences are recognizable. For example, the information about the start and the end of a task is stored in the JC3IEDM under the attributes “action-task-start-qualifier-code”, “action-task-planned-start-datetime”, “actiontask-end-qualifier-code”, and “action-taskplanned-end-datetime”. This means that, in JC3IEDM, the When is structurally part of the What. In the 5W-paradigm, What and When are independent constituents, a categorization decision mirrored by C2LG. Additionally, in JC3IEDM neither the qualifier and the date/time for a task’s start, nor the qualifier and the date/time for a task’s end are grouped together. All four data entries are attribute value pairs in the “action task” table, independent of each other. In contrast, in C2LG, “action-task-startqualifier-code” and “action-task-planned-start-

datetime” constitute the StartWhen constituent, while “action-task-end-qualifier-code”, and “action-task-planned-end-datetime” constitute the EndWhen constituent.

5

Conclusion

A C2 Language has to be a formal language so that it can be processed automatically. Formal languages always have a grammar. Even if “only” an XML schema is used to define a formal C2 language, that schema is the language’s grammar. Our approach does not start with the schema, which is the directly applicable manifestation of the grammar, but rather starts on the formal theoretical side. We take principles from the field of linguistics to guide the construction of the grammar. This approach ensures that expressions from the resulting language can be processed. The grammar that we propose is a context-free grammar, the C2LG. C2LG had been the basis from which the schemata had been derived that were used in the experiments and demonstrations performed by NATO RTO MSG-048 “Coalition BML”. The success of these experiments demonstrates both the value of our approach and the value of the C2LG.

6

References

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Author Biographies ULRICH SCHADE is a Senior Scientist at the Fraunhofer Institute for Communication, Information Processing and Ergonomics and is associate professor to the Institute for Communication Science, Bonn University. He is an expert in computational linguistics and has contributed to the understanding of how formal grammar can improve the development of BML. MICHAEL HIEB is an Associate Research Professor with the Center of Excellence in C4I at George Mason University. He was the Co-Chair of the SISO C-BML Study Group and led the team that developed the initial BML concept for the US. Dr. Hieb is a technical advisor for the Simulation to C4I Overarching Integrated Product Team in the US Army. He received his PhD in Information Technology at George Mason University in 1996, developing an instructable Modular SemiAutomated Forces agent.