{
    "paper_id": "M92-1034",
    "header": {
        "generated_with": "S2ORC 1.0.0",
        "date_generated": "2023-01-19T03:13:18.716580Z"
    },
    "title": "PRC Inc: DESCRIPTION OF THE PAKTUS SYSTE M USED FOR MUC-4",
    "authors": [
        {
            "first": "Bruce",
            "middle": [],
            "last": "Loatman",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "PRC Inc . Technology Division",
                "location": {
                    "addrLine": "1500 PRC Drive McLean",
                    "postCode": "22102",
                    "region": "VA"
                }
            },
            "email": "loatman_bruce@po.gis.prc.com"
        }
    ],
    "year": "",
    "venue": null,
    "identifiers": {},
    "abstract": "BACKGROUND The PRC Adaptive Knowledge-based Text Understanding System (PAKTUS) has been unde r development as an Independent Research and Development project at PRC since 1984. It includes a core English lexicon and grammar, a concept network, processes for applying these to lexical, syntactic, semantic, and discourse analysis, and tools that support the adaptation of the generi c core to new domains, primarily by acquiring sublanguage and domain-specific lexicon and conceptual topic patterns of interest. The lexical, syntactic, and semantic analysis components were completed before MUC-4 and required little adaptation. The discourse analysis component is new and was completed in the course of applying the system to MUC-4, although it is generic. The overall system is described in [1]. The present description concentrates on discourse analysis.",
    "pdf_parse": {
        "paper_id": "M92-1034",
        "_pdf_hash": "",
        "abstract": [
            {
                "text": "BACKGROUND The PRC Adaptive Knowledge-based Text Understanding System (PAKTUS) has been unde r development as an Independent Research and Development project at PRC since 1984. It includes a core English lexicon and grammar, a concept network, processes for applying these to lexical, syntactic, semantic, and discourse analysis, and tools that support the adaptation of the generi c core to new domains, primarily by acquiring sublanguage and domain-specific lexicon and conceptual topic patterns of interest. The lexical, syntactic, and semantic analysis components were completed before MUC-4 and required little adaptation. The discourse analysis component is new and was completed in the course of applying the system to MUC-4, although it is generic. The overall system is described in [1]. The present description concentrates on discourse analysis.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Abstract",
                "sec_num": null
            }
        ],
        "body_text": [
            {
                "text": "The overall structure and operation of PAKTUS are shown in Figure 1 . Processing proceed s mostly sequentially through preprocessing (the decomposition of the text stream into individua l messages, message segments , sentences, and words), lexica l analysis (morphological analysis and mapping of words into entries in th e lexicon which contain information about their syntax and semantics) , syntactic analysis (using a parser an d grammar), semantic analysi s (mapping the syntactic structures into conceptual frames with roles fille d by phrase constituents), discours e analysis (identification of discours e topics and noun phrase reference), Figure 1 . PAKTUS Architecture and finally extraction of information from discourse structures into domain-specific templates . The primary exception to sequential control flow is the interaction between the syntactic and semantic components at the clause and noun phrase level . This results in essentially deterministic parsing in linear time : the first syntactico-semantically successful parse of a sentence is accepted ; others are never generated. Moreover, parse time is restricted, and the longest substring, along with any initial substring successfully parsed, is returned when parse time is exhausted . Figure 2 shows the discourse analysis module, which was first used for MUC-4, and it s interaction with the extraction module . The discourse module is generic for expository text, suc h as news reports. In figure 2, only the conceptual patterns and filter are MUC-4-specific, and these are part of the extraction component, not discourse analysis .",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 59,
                        "end": 67,
                        "text": "Figure 1",
                        "ref_id": null
                    },
                    {
                        "start": 649,
                        "end": 657,
                        "text": "Figure 1",
                        "ref_id": null
                    },
                    {
                        "start": 1263,
                        "end": 1271,
                        "text": "Figure 2",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "APPROACH",
                "sec_num": null
            },
            {
                "text": "Common\u00b0\"\u00b0`Y",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Semantic Structures",
                "sec_num": null
            },
            {
                "text": "Role Filler & Times?",
                "cite_spans": [],
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                "eq_spans": [],
                "section": "LO -11D",
                "sec_num": null
            },
            {
                "text": "The discourse module operates on the semantic structures (case frames) produced by the semantic analysis module. It builds topic structures consisting of sets of case frames that have common topic objects and times. Topic objects are defined as fillers of certain case roles, specifically, 16 of the total 40 case roles used in PAKTUS, as illustrated in Figure 3 . The most notable case role that is excluded as a topic object is the Agent. This is because topic structures are meant to represent information about entities that are being affected or focused upon in some way , whereas a single Agent can operate on several different entities . An example below, from the MUC-4 corpus, will clarify the importance of excluding the Agent as a topic role .",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 354,
                        "end": 362,
                        "text": "Figure 3",
                        "ref_id": "FIGREF0"
                    }
                ],
                "eq_spans": [],
                "section": "Figure 2. Discourse Analysis and Extraction Detail s",
                "sec_num": null
            },
            {
                "text": "A side effect of comparing topic objects for commonality, is that some noun phrases (NPs) will be unified (i .e., considered by discourse analysis to have the same referent) . It is possible (actually quite common) for two NPs to be considered common topic objects, but not be unifie d (e.g., in one MUC-4 passage, PAKTUS considers \"crime\" and \"killing\" to have topi c commonality, but does not unify them since \"crime\" is more general) .",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Figure 2. Discourse Analysis and Extraction Detail s",
                "sec_num": null
            },
            {
                "text": "After all case frames have been assigned to topic structures, domain-specific conceptua l patterns are compared to the case frames, topic-by-topic, binding pattern variables to informatio n that is extracted and put into event reports whose format is specified by a domain-specific template .",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Figure 2. Discourse Analysis and Extraction Detail s",
                "sec_num": null
            },
            {
                "text": "The NP unifications assist in this process, effectively consolidating information that may be widel y dispersed in the text. Note that a single topic structure may contain information on multiple events. The final step in the extraction process is to filter and merge the event reports (e.g., for MUC-4, ignoring events that are too old, and merging events that can not be distinguished in time o r location), and format the results to the output file. ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Figure 2. Discourse Analysis and Extraction Detail s",
                "sec_num": null
            },
            {
                "text": "Message number 48 from the \"test2\" set, which is reprinted in Appendix F, will be used t o illustrate PAKTUS's operation for MUC-4 . PAKTUS processes text sequentially, first strippin g off the document header, then identifying sentences, which are processed syntactico-semanticall y one at a time, after which all the results are passed to the discourse component . Figure 4 shows the raw, unprocessed text of the first sentence (Si), followed by its lexica l analysis . Each word has one or more senses, represented as a root symbol, which is generally the concatenation of the English token, the \"^\" character, and the PAKTUS lexical category (e .g., \"Condemn^Monotrans\"), or as a simple structure involving a root, lexical category, inflectional mark, and sometimes a conceptual derivation (e .g. the structure \"(Condemn^Monotrans L^Effectmark Base C^It-got)\" represents the adjective sense of \"condemned\") . For each word, all senses in the PAKTUS lexicon are fetched or derived at this time ; disambiguation is generally delayed until the syntactic and semantic phases . The syntactic and conceptual analyses of this sentence are shown in Figure S . Note that conceptual structures are produced for some nouns (notably here, \"killing\"), not just for verbs . These conceptual structures are essential to the overall task of information extraction ; if no case frames are produced for a sentence (i .e., the syntactico-semantic analysis failed), it is completel y ignored by the discourse analysis and extraction processes .",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 367,
                        "end": 375,
                        "text": "Figure 4",
                        "ref_id": "FIGREF2"
                    },
                    {
                        "start": 1145,
                        "end": 1153,
                        "text": "Figure S",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "EXAMPLE OF MUC-4 DOCUMENT PROCESSIN G",
                "sec_num": null
            },
            {
                "text": "The syntactic analysis produced for Si is a configuration of syntactic registers (the main one s are shown in the figure) and register fillers . In this case, the main clause has a Main-Ver b (condemned), Subject (the NP whose Head is Cristiani), and Direct Object (the terrorist killin g NP). The conjoined clause (\"and accused the FMLN . . .\") was correctly parsed, and its gap (no explicit Subject) has been filled in with the Subject of the main clause .",
                "cite_spans": [],
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                "eq_spans": [],
                "section": "CONDEMN^MONOTRANS L A MONOTRANS S A ED) ) (THE ADET) (TERRORIST^PERSON ) ((KILL^MONOTRANS L A MONOTRANS S^ING ) (KILLAMONOTRANS L A ABSTRACT BASE C^ACT-OF ) (KILLAMONOTRANS L A ADJ BASE C A DOES) ) (OF^PARTICLE OF^PREP) (ATTORNEY\\ GENERAL^SPECIALIST ) (ROBERTO A MALE) (GARCIA A PERSON) (ALVARADO A PERSON ) (AND^CONJ ) ((ACCUSE A MONOTRANS L^EFFECT-MARK BASE C^IT-GOT ) (ACCUSE A MONOTRANS L AMONOTRANS S^ED) ) (THE^DET ) (FARABUNDO\\ MARTI\\ NATIONAL\\ LIBERATION\\ FRONT A TERRORIST -GROUP ) (OF^PARTICLE OF A PREP) (THE A DET) (CRIME^ACTIVITY) )",
                "sec_num": null
            },
            {
                "text": "PAKTUS produced four case frames for S1, one for each of the two clauses, one for the \"killing\" NP and one for the \"crime\" NP .",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "CONDEMN^MONOTRANS L A MONOTRANS S A ED) ) (THE ADET) (TERRORIST^PERSON ) ((KILL^MONOTRANS L A MONOTRANS S^ING ) (KILLAMONOTRANS L A ABSTRACT BASE C^ACT-OF ) (KILLAMONOTRANS L A ADJ BASE C A DOES) ) (OF^PARTICLE OF^PREP) (ATTORNEY\\ GENERAL^SPECIALIST ) (ROBERTO A MALE) (GARCIA A PERSON) (ALVARADO A PERSON ) (AND^CONJ ) ((ACCUSE A MONOTRANS L^EFFECT-MARK BASE C^IT-GOT ) (ACCUSE A MONOTRANS L AMONOTRANS S^ED) ) (THE^DET ) (FARABUNDO\\ MARTI\\ NATIONAL\\ LIBERATION\\ FRONT A TERRORIST -GROUP ) (OF^PARTICLE OF A PREP) (THE A DET) (CRIME^ACTIVITY) )",
                "sec_num": null
            },
            {
                "text": "This conceptual analysis will enable the discourse analysis module to determine that \"the crime \" refers to \"the killing\" because 1) both are topic objects (as fillers of Focus roles), 2) \"crime's \" concept CAAGGR is a generalization of \"the killing's\" concept of CAKILL in the PAKTUS conceptual network, and 3) \"crime\" appears in a subordinate clause (all three conditions are required for this reference resolution) .",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "CONDEMN^MONOTRANS L A MONOTRANS S A ED) ) (THE ADET) (TERRORIST^PERSON ) ((KILL^MONOTRANS L A MONOTRANS S^ING ) (KILLAMONOTRANS L A ABSTRACT BASE C^ACT-OF ) (KILLAMONOTRANS L A ADJ BASE C A DOES) ) (OF^PARTICLE OF^PREP) (ATTORNEY\\ GENERAL^SPECIALIST ) (ROBERTO A MALE) (GARCIA A PERSON) (ALVARADO A PERSON ) (AND^CONJ ) ((ACCUSE A MONOTRANS L^EFFECT-MARK BASE C^IT-GOT ) (ACCUSE A MONOTRANS L AMONOTRANS S^ED) ) (THE^DET ) (FARABUNDO\\ MARTI\\ NATIONAL\\ LIBERATION\\ FRONT A TERRORIST -GROUP ) (OF^PARTICLE OF A PREP) (THE A DET) (CRIME^ACTIVITY) )",
                "sec_num": null
            },
            {
                "text": "Determining that the crime refers to the killing here is important ; it enables PAKTUS to identify the FMLN as the accused perpetrator of Alvarado's killing . It can also determine that the accusation is made by an authority (president-elect Cristiani), thanks to the gap filling by th e syntactic analysis. ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "CONDEMN^MONOTRANS L A MONOTRANS S A ED) ) (THE ADET) (TERRORIST^PERSON ) ((KILL^MONOTRANS L A MONOTRANS S^ING ) (KILLAMONOTRANS L A ABSTRACT BASE C^ACT-OF ) (KILLAMONOTRANS L A ADJ BASE C A DOES) ) (OF^PARTICLE OF^PREP) (ATTORNEY\\ GENERAL^SPECIALIST ) (ROBERTO A MALE) (GARCIA A PERSON) (ALVARADO A PERSON ) (AND^CONJ ) ((ACCUSE A MONOTRANS L^EFFECT-MARK BASE C^IT-GOT ) (ACCUSE A MONOTRANS L AMONOTRANS S^ED) ) (THE^DET ) (FARABUNDO\\ MARTI\\ NATIONAL\\ LIBERATION\\ FRONT A TERRORIST -GROUP ) (OF^PARTICLE OF A PREP) (THE A DET) (CRIME^ACTIVITY) )",
                "sec_num": null
            }
        ],
        "back_matter": [],
        "bib_entries": {},
        "ref_entries": {
            "FIGREF0": {
                "type_str": "figure",
                "text": "Case Roles Determining Topic Objects in PAKTU S",
                "num": null,
                "uris": null
            },
            "FIGREF1": {
                "type_str": "figure",
                "text": "raw sentence : SALVADORAN PRESIDENT-ELECT ALFREDO CRISTIANI CONDEMNED TH E TERRORIST KILLING OF ATTORNEY GENERAL ROBERTO GARCIA ALVARADO AN D ACCUSED THE FARABUNDO MARTI NATIONAL LIBERATION FRONT (FMLN) OF TH E CRIME .",
                "num": null,
                "uris": null
            },
            "FIGREF2": {
                "type_str": "figure",
                "text": "Lexical Analysis of the First Sentence of Test2 Document Number 48",
                "num": null,
                "uris": null
            },
            "FIGREF3": {
                "type_str": "figure",
                "text": "Figure 5. Syntactic and Conceptual Analysis of S i",
                "num": null,
                "uris": null
            },
            "FIGREF4": {
                "type_str": "figure",
                "text": "Template Fills for Test2 Report 4",
                "num": null,
                "uris": null
            },
            "TABREF0": {
                "type_str": "table",
                "num": null,
                "html": null,
                "text": "",
                "content": "<table/>"
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        }
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