{ "paper_id": "M92-1017", "header": { "generated_with": "S2ORC 1.0.0", "date_generated": "2023-01-19T03:13:13.161057Z" }, "title": "THE PRC PAKTUS SYSTEM : MUC-4 TEST RESULTS AND ANALYSI S", "authors": [], "year": "", "venue": null, "identifiers": {}, "abstract": "In commenting on PRC's performance in MUC-3, we reported [1] that the component of ou r system that could most improve performance was discourse analysis. The MUC-4 exercise has strongly confirmed that view. We added a new discourse module to PAKTUS, made very fe w changes to the other system components, and the result was significantly improved performance. This paper discusses our test results, what we focused on for this task, what worked well, and what would improve performance further. A companion paper in this volume describes how ou r system functions.", "pdf_parse": { "paper_id": "M92-1017", "_pdf_hash": "", "abstract": [ { "text": "In commenting on PRC's performance in MUC-3, we reported [1] that the component of ou r system that could most improve performance was discourse analysis. The MUC-4 exercise has strongly confirmed that view. We added a new discourse module to PAKTUS, made very fe w changes to the other system components, and the result was significantly improved performance. This paper discusses our test results, what we focused on for this task, what worked well, and what would improve performance further. A companion paper in this volume describes how ou r system functions.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Abstract", "sec_num": null } ], "body_text": [ { "text": "The PRC PAKTUS system used for MUC-4 is essentially the same linguistic system that w e used for MUC-3, with the addition of a generic discourse analysis module . PAKTUS applies lexical, syntactic, semantic, and discourse analysis to all text in each document. The linguistic modules for this are nearly independent of the task domain (i .e., MUC-4, but some of the datalexical entries, and a few grammar rules -are tuned for the MUC-4 text corpus). Task-specific template filling and filtering operations are performed only after linguistic analysis is completed .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "KEY SYSTEM FEATURE S", "sec_num": null }, { "text": "The task-specific patterns that determine what to extract from the discourse structures wer e only minimally defined due to the limited time and effort available . The other task-specific additions to the system were the location set list, and functions for better recognizing time and location of events.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "KEY SYSTEM FEATURE S", "sec_num": null }, { "text": "Figure 1 summarizes PRC's scores for MUC-4. The scoring notation is explained in Appendix G. Overall, we were pleased with the performance improvement since MUC-3, whic h was obtained with only about 4 person months of linguistic development effort, little of which wa s specific to the MUC-4 task. The most significant new development, compared to our MUC-3 system, is the addition of the discourse analysis module . This module is generic for expository discourse such as is found in news reports. Application-specific extraction requirements ar e maintained separately from the discourse module, are applied only after it executes, and were minimally specified for MUC-4.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "RESULT S", "sec_num": null }, { "text": "Our system generally had much better precision than recall in these tests . We expected this because it uses complete linguistic analysis designed for text understanding, and because it ha s only a very limited amount of task-specific knowledge . For example, its discourse analysi s module was trained on only 8 of the MUC-4 pre-test corpus of 1500 reports . For these sam e reasons, we also expected a high degree of corpus independence, and this was supported by the similarity of scores on TST3 and TST4.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "RESULT S", "sec_num": null }, { "text": "The main limiting factors for PRC were time and availability of people for development. We directed most of our energies to generic linguistic development, and the linguistic aspects of th e task have essentially been completed . Because we had little time remaining to devote to MUC-4specific issues, however, much of the information that PAKTUS produced through syntactic , semantic, and discourse analysis did not find its way into the template fills . ", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "RESULT S", "sec_num": null }, { "text": "-------------------------------------------------------------------------- TST3 MATCHED/", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "POS ACTICOR PAR INCIICR IPAISPU MIS NONIREC PRE OVG FAL", "sec_num": null }, { "text": "------------------------------------------------------------------------- TST Q MATCHED/", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": ".8 6", "sec_num": "24" }, { "text": "Three PRC researchers participated in linguistic development that contributed to MUC-4 performance. Most of this development was generic, however, and will support applications other than MUC-4. Figure 2 shows an estimate of our level of effort broken down by linguistic task. Our total linguistic development effort was about four months, with almost 40% of that on discourse analysis . Significant effort also went into time and location grammar functions, although this is small compared to the prior effort that went into the overall grammar.", "cite_spans": [], "ref_spans": [ { "start": 195, "end": 203, "text": "Figure 2", "ref_id": null } ], "eq_spans": [], "section": "DEVELOPMENT EFFORT", "sec_num": null }, { "text": "Lexicon entry was minimal, consisting primarily of semi-automatic entry of the MUC-4 location set list. Many words from the MUC-4 corpus have never been entered into the PAKTU S lexicon. Instead, heuristics based on word morphology make guesses about these unrecognized words.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "DEVELOPMENT EFFORT", "sec_num": null }, { "text": "The specific changes and additions to the PAKTUS knowledge bases for MUC-4 are enumerated in Figure 3 . Most of the lexical additions were from the MUC-4 location set list . These were added semi-automatically in batch mode. Other lexical additions were based on short lists of exceptions to our unknown word heuristics, derived by scanning traces from the entir e 1500 document MUC-4 pre-test corpus .", "cite_spans": [], "ref_spans": [ { "start": 93, "end": 101, "text": "Figure 3", "ref_id": "FIGREF1" } ], "eq_spans": [], "section": "DEVELOPMENT EFFORT", "sec_num": null }, { "text": "- Figure 2 . Breakdown of Linguistic Development Efforts One notable area that would have significantly improved performance was the definition o f MUC-4-specific conceptual patterns . These are used to extract information from the discourse structures. Very little was done here, however, due to limited time and resources . Only 88 of these patterns were added . We had intended to define several hundred, but that would have required about another month of effort. ", "cite_spans": [], "ref_spans": [ { "start": 2, "end": 10, "text": "Figure 2", "ref_id": null } ], "eq_spans": [], "section": "DEVELOPMENT EFFORT", "sec_num": null }, { "text": "As already noted, the most significant system improvement was in discourse analysis . The new discourse module was trained on only 8 documents from the test2 set . These were documents 1, 3, 10, 11, 48, 63, 99, and 100 . The time and location grammar and functional changes were based on manual analysis of the 100 test2 documents . The entire pre-test corpus was scanne d automatically to identify words missing from our lexicon, but only a few of these were enteredthose more common words that did not conform to our unrecognized word heuristics .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SYSTEM TRAINING AND PERFORMANCE IMPROVEMENT", "sec_num": null }, { "text": "The improvement in PAKTUS's linguistic performance from MUC-3 up to the day of testin g for MUC-4 can be seen in Figure 4 , derived from the test runs on the test2 corpus, using the Fmeasure specified for MUC-4. The development was carried out during April and May, 1992 .", "cite_spans": [], "ref_spans": [ { "start": 113, "end": 121, "text": "Figure 4", "ref_id": "FIGREF2" } ], "eq_spans": [], "section": "SYSTEM TRAINING AND PERFORMANCE IMPROVEMENT", "sec_num": null }, { "text": "The basic functionality of the new discourse module was completed on May 6, and i t dramatically improved performance. This module has two main functions : 1) it builds discourse topic structures, and 2) it unifies noun phrases that refer to the same entity . There is a rather intricate interaction between these two functions, and this had to be carefully developed over th e next ten days (through May 17), so that improvement in one function did not impair the other . After completion of the two basic discourse functions, enhancements (pronoun reference, etc .) were added to the discourse module, through May 25 . This allowed only three days for MUC-4specific knowledge to be added that could take advantage of the new discourse module .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SYSTEM TRAINING AND PERFORMANCE IMPROVEMENT", "sec_num": null }, { "text": "It can be seen from figure 4 that, once the discourse functions were properly integrated (o n May 17), performance improvement averaged one point per day over the last eleven days befor e official MUC-4 testing . We believe that the system is far from the limit of its extraction capabilit y based on its existing linguistic components . This belief is supported by the ease with which we improved performance on the MUC-4 conference walkthrough document (test2, document 48) b y adding a few MUC-4-specific conceptual patterns . ", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SYSTEM TRAINING AND PERFORMANCE IMPROVEMENT", "sec_num": null }, { "text": "Almost all of PAKTUS is generic and can be applied to other applications . All of its processes, including the new discourse analysis module, are generic . They operate on a set of object-oriented knowledge bases, some of which are generic (common English grammar and lexicon) and some of which are domain-specific (conceptual templates).", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REUSABILITY OF THE SYSTE M", "sec_num": null }, { "text": "The primary tasks in applying PAKTUS to a new domain or improving its performance in an existing domain, are lexicon addition and conceptual template specification, both of which ar e relatively easy (compared to changing the grammar, for example) .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REUSABILITY OF THE SYSTE M", "sec_num": null }, { "text": "Two other tasks that must be done, but only once for each new domain, are specifying th e input document formats, and the output specifications. These are template-driven in PAKTUS . For MUC-4 we used the template supplied by NRaD, adding a function for each template slot to gather information from our generic discourse data structures .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REUSABILITY OF THE SYSTE M", "sec_num": null }, { "text": "We learned that the current implementation of PAKTUS, including the new discourse module , is robust and adaptable. The more complex components (syntactic, semantic, and discours e analysis modules) are stable and competent enough to apply the system to different domains an d produce useful results, by adding domain-specific knowledge (lexicon and conceptual patterns) . We were particularly pleased to learn that it was not necessary to manually analyze much of th e corpus in detail . This was done for only eight documents for MUC-4. The full development corpus was used only for lexicon development and testing the system for overall performance an d logic errors.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "WHAT WE LEARNE D About PAKTUS", "sec_num": null }, { "text": "MUC-4 reinforced our appreciation of the importance of clearly defined output specifications , and the utility of having answer keys against which to measure the system's progress . We are already using the MUC-4 task specifications as a model for a new application of our system .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "About the Tas k", "sec_num": null }, { "text": "We have also come to appreciate the utility of an automated scoring program to the development effort. This quickly eliminates much uncertainty about whether a new development i s useful or not, and thereby speeds system development.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "About the Tas k", "sec_num": null }, { "text": "It is difficult to define evaluation measures for a task of this nature . Although the MUC-4 measures seem better than those of MUC-3, they do not accurately convey the true performance in some situations . For example, the system might correctly fill in 75% of the information for a template, but not report it because it got the wrong date (events over three months old are no t reported), or the wrong country . We would prefer to report all incidents, with an extra slot indicating whether they are considered relevant or not. This seems more appropriate for evaluatin g linguistic competence . We also suspect that many analysts using such a system would like to be able to identify \"irrelevant\" incidents, especially since, given the current limits of linguistic technology, they may be relevant after all .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "About Evaluatio n", "sec_num": null }, { "text": "[1] Kariya, C, \"PRC PAKTUS : MUC-3 Test Results and Analysis\", Proceedings of the 3rd Message Understanding Conference, San Mateo, CA: Morgan Kaufmann, 1991 .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REFERENC E", "sec_num": null }, { "text": ".84 29 .79", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null } ], "back_matter": [], "bib_entries": {}, "ref_entries": { "FIGREF0": { "uris": null, "num": null, "type_str": "figure", "text": "PRC Score Summary" }, "FIGREF1": { "uris": null, "num": null, "type_str": "figure", "text": "Additions/ Modifications to PAKTUS Knowledge Bases for MUC-4" }, "FIGREF2": { "uris": null, "num": null, "type_str": "figure", "text": "Performance Improvement During Developmen t" } } } }