{ "paper_id": "M91-1016", "header": { "generated_with": "S2ORC 1.0.0", "date_generated": "2023-01-19T03:15:35.775066Z" }, "title": "SYNCHRONETICS : MUC-3 TEST RESULTS AND ANALYSI S", "authors": [ { "first": "James", "middle": [], "last": "Mayfiel", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Edwin", "middle": [], "last": "Addison", "suffix": "", "affiliation": {}, "email": "" } ], "year": "", "venue": null, "identifiers": {}, "abstract": "The Synchronetics entry in the MUC-3 competition is a full-parser, semantic net-based system written i n C. Our system attempts to fill the first four slots of each template and, in some cases, the three perpetrato r slots and the human-target-ids slot. The Synchronetics system achieved the following official scores on the tst2 corpus :", "pdf_parse": { "paper_id": "M91-1016", "_pdf_hash": "", "abstract": [ { "text": "The Synchronetics entry in the MUC-3 competition is a full-parser, semantic net-based system written i n C. Our system attempts to fill the first four slots of each template and, in some cases, the three perpetrato r slots and the human-target-ids slot. The Synchronetics system achieved the following official scores on the tst2 corpus :", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Abstract", "sec_num": null } ], "body_text": [ { "text": "These official results were achieved despite a system bug that caused almost half of the roughly 1400 sentences in the corpus to be thrown away without being processed at all . The bug arose because a buffer that was supposed to be 200 items long was inadvertantly changed to be 20 items long . With this bug fixed, w e achieved the following unofficial scores : ", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "0 * * 0 ------------------------------------ MATCHED ONLY 20 54 2 6 MATCHED/MISSING", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SLOT REC PRE OVG FA L ------------------------------------", "sec_num": null }, { "text": "10 54 2 6 ALL TEMPLATES 10 33 5 5 SET FILLS ONLY 11 62 13 0", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SLOT REC PRE OVG FA L ------------------------------------", "sec_num": null }, { "text": "We do not at present have any settings that can be modified to alter the recall/precision tradeoff .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SLOT REC PRE OVG FA L ------------------------------------", "sec_num": null }, { "text": "The most time-consuming of our activities were the development of the semantic net software, and th e development of the phrase and sentence interpreters . Next came the development of the grammars for th e two parsers, and the template generation software . Development of the dictionary was quite rapid, thank s to our automatic acquisition software . The activity we spent the least amount of time on was the encodin g of world knowledge into the knowledge base .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "ALLOCATION OF TIM E", "sec_num": null }, { "text": "Our primary limiting factor was the tenuous nature of the lines of communication between our team members . With personnel spread across six different sites, we were forced to rely on weekly meetings to resolve problem s that would ordinarily be cleared up on a daily basis if everyone were working at the same site .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "LIMITING FACTOR S", "sec_num": null }, { "text": "The second limiting factor for our system was the amount of time we had available to us . Most of the system was developed from scratch (only the NL-Builder software was written prior to the commencemen t of our project) . We had only a few weeks between the time we were first able to process 100 texts and th e time that the final test was due . Thus, we were unable to be as careful as we would have liked to be in th e development of the final system configuration .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "LIMITING FACTOR S", "sec_num": null }, { "text": "The third limiting factor for our system was the lack of a detailed and well thought out world model . We did most of our development using a very small world model that had fewer than 50 concepts . Jus t before running the final test, we quickly developed and switched to a world model containing almost 90 0 concepts . However, we did not have time to examine it closely before running the test . We believe that we could considerably increase our system's performance for the slots we are currently filling by improving th e world model .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "LIMITING FACTOR S", "sec_num": null }, { "text": "Our biggest successes were the development of the dictionary, and the speed of the parsers . Our automati c acquisition software allowed us to obtain a dictionary of 10000 words quite painlessly . Together, both parsers took less than one hour to process every word of all 100 texts, running on a DecStation 3100 .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SUCCESSES AND FAILURE S", "sec_num": null }, { "text": "Our biggest failures were lack of development of the knowledge base and the speed of the semantic net I/ O routines . Our knowledge base was a last-minute effort, which significantly degraded system performance . The semantic net I/O routines were slow enough to be the main time drain on the three non-parser components . For these reasons the knowledge base and the semantic net I/O routines are our prime candidates to b e rewritten .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SUCCESSES AND FAILURE S", "sec_num": null }, { "text": "We expect to be able to reuse all system components except for the template generator in other projects . We are currently working on a project to automatically convert linear text to hypertext . We plan to use ou r MUC system as the front end to the conversion system . This will require only the development of software to generate hypertext links based on the semantic net built by the MUC system, and the development of a new knowledge base for the target domain .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REUSABILITY", "sec_num": null }, { "text": "Participation in MUC-3 has led us to the following conclusions :", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "LESSONS LEARNE D", "sec_num": null }, { "text": "\u2022 Our software engineering paradigm (which is thrust upon us by virtue of the fact that our personne l are spread out across several sites) is a poor one, but it is not fatal .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "LESSONS LEARNE D", "sec_num": null }, { "text": "\u2022 Several person-years of work is needed to build a parser-based system that has the poieniial to do well at the MUC task . Even then, a weakness in any component can easily reduce the system's abilities t o those of a stupid keyword-matching system .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "LESSONS LEARNE D", "sec_num": null }, { "text": "\u2022 Evaluation of natural language processing systems through a MUC-like competition is significantl y complicated by the fact that it is hard to know what is being measured . Nonetheless, we believe that our architecture will be excellent for evaluation of the various components of a natural languag e processing system, because we will be able to mix and match the components that go into our system . We will have this flexibility because each of our components is a stand-alone program, and because al l of our programs communicate with each other via the same semantic net representation language . Fo r example, if we develop both a script-processing component and an anaphora component, we will be abl e to put them together in either order, or omit either or both of them . By comparing the results of eac h of these configurations, we will gain insight into the relative merits of these two forms of processing .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "LESSONS LEARNE D", "sec_num": null } ], "back_matter": [], "bib_entries": {}, "ref_entries": {} } }