{ "paper_id": "M91-1002", "header": { "generated_with": "S2ORC 1.0.0", "date_generated": "2023-01-19T03:15:24.560433Z" }, "title": "MUC-3 EVALUATION METRIC S", "authors": [ { "first": "Nancy", "middle": [], "last": "Chinchor", "suffix": "", "affiliation": { "laboratory": "", "institution": "Science Applications International Corporatio n", "location": { "addrLine": "10260 Campus Point Drive, M/S 1 2", "postCode": "9212", "settlement": "San Diego", "region": "CA" } }, "email": "" } ], "year": "", "venue": null, "identifiers": {}, "abstract": "", "pdf_parse": { "paper_id": "M91-1002", "_pdf_hash": "", "abstract": [], "body_text": [ { "text": "The MUC-3 evaluation metrics are measures of performance for the MUC-3 template fill task . Obtaining summary measures of performance necessitates the los s of information about many details of performance . The utility of summary measure s for comparison of performance over time and across systems should outweigh thi s loss of detail . The template fill task is complex because of the varying nature of th e fills for each slot and the interdependencies of the slots . The evaluation metrics used in MUC-3 were adapted from traditional measures in information retrieval and signa l procesing and were still evolving to fit the more complex data extraction task of MUC -3 when the evaluation was performed . The scoring of the template fill task and th e calculation of the metrics used in MUC-3 will be described here . This description i s meant to assist in the analysis of the MUC-3 results and in the further evolution of the evaluation metrics .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Purpos e", "sec_num": null }, { "text": "The measures of performance chosen for use in MUC-3 were recall, precision , fallout, and overgeneration .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Metric s", "sec_num": null }, { "text": "Recall, precision, and fallout were adapted based o n their use in information retrieval . Overgeneration was developed as a measure fo r MUC-3 . Recall is a measure of the completeness of the template fill . Precision is a measure of the accuracy of the fill . Fallout is a measure of the false alarm rate fo r the slots which can be filled from finite sets of slot fillers .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Metric s", "sec_num": null }, { "text": "Overgeneration is a measure of spurious generation . These measures will be described in greater detai l below .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Metric s", "sec_num": null }, { "text": "A semi-automated scoring system was developed for MUC-3 . The scorin g system displayed the answer key templates, the response templates, and the message s using a flexibly customized emacs interface . During scoring, the user was asked to enter the score for displayed mismatches between the key and the respons e templates . Fills could generally be scored as matches, partial matches, or mismatches . Depending on the type of slot fill, the scoring system may or may not have allowe d full credit to be given .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SCORE REPORT", "sec_num": null }, { "text": "The interactive scoring was carried out following welldefined scoring guidelines .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SCORE REPORT", "sec_num": null }, { "text": "Depending on the scoring guidelines, full, partial, or n o credit may have been allowed for each mismatch .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SCORE REPORT", "sec_num": null }, { "text": "After the interactive scoring wa s complete, the scoring system produced an official score report containing template by template score reports and a summary score report for the official record .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SCORE REPORT", "sec_num": null }, { "text": "A sample summary score report produced for human comparison against the ke y appears in Figure 1 . The following sections discuss the contents of the score report . ", "cite_spans": [], "ref_spans": [ { "start": 88, "end": 96, "text": "Figure 1", "ref_id": null } ], "eq_spans": [], "section": "SCORE REPORT", "sec_num": null }, { "text": "Individual slot fills in the response were scored as correct, partially correct , incorrect, noncommittal, spurious, or missing . A response was correct if it was th e same as the key, partially correct if it partially approximated the key, and incorrec t if it was not the same as the key .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Scoring Categorie s", "sec_num": null }, { "text": "If the key and response were both blank, th e response was scored as noncommittal . If the key was blank but the slot was filled, th e response was scored as spurious . If the response was blank and the key was not, th e response was scored as missing . Figure 2 summarizes the scoring categories relatin g them to the corresponding columns in the score report . The summary score report rows show the totals for each of the categories ove r all templates . The slots are listed on the left hand side and the totals for each slot ove r all templates are given in the labeled columns .", "cite_spans": [], "ref_spans": [ { "start": 254, "end": 262, "text": "Figure 2", "ref_id": null } ], "eq_spans": [], "section": "Scoring Categorie s", "sec_num": null }, { "text": "For example, the total number o f physical targets correctly identified was 54 . The number appears in the phys-targetids row and the COR column of the summary score report . Note that the bottom fou r rows of the score report are not slot scores but rather global summary rows describe d in a later section .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Category", "sec_num": null }, { "text": "During scoring, the scoring system automatically scored matches as correc t and some partially matching hierarchically organized items as partially correct . However, many of the mismatches were interactively scored by the user . To reflec t the number of items interactively scored as correct or partially correct, two column s labeled ICR and IPA were provided .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Category", "sec_num": null }, { "text": "The first two columns in the score report contain the number of possible slo t fills (POS) and the actual number of slot fills (ACT) . The number of possible slot fill s is the number of slots fills in the key plus the number of optional slot fills in the ke y that were matched in the response . The number of possible slot fills for each syste m differs depending on the optional fills given by the system . The number of actua l fills given is the number of slot fillers in the response . The numbers in the possible and actual columns are used to calculate the metrics .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Category", "sec_num": null }, { "text": "The metrics were calculated for each slot and for the summary rows . Th e calculations were based on information in the columns of the score report as well a s on some tallies kept internally by the scoring system . The first three metrics show n in the score report are recall, precision, and overgeneration .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Calculation of Metric s", "sec_num": null }, { "text": "These were calculate d for each slot and were based on information contained in the score report .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Calculation of Metric s", "sec_num": null }, { "text": "Recall is a measure of completeness and was calculated as follows .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Calculation of Metric s", "sec_num": null }, { "text": "correct + (partial x 0.5) possible", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Calculation of Metric s", "sec_num": null }, { "text": "For example, recall for the human-target-ids slot was calculated as follows . Fallout is a measure of the false alarm rate . The number of false alarms coul d only be measured for slots for which we knew the number of possible incorrec t responses .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Calculation of Metric s", "sec_num": null }, { "text": "A subset of the slots in the template fill task were filled from finite sets . The rest of the slots are filled from possibly infinite sets .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REC", "sec_num": null }, { "text": "Fallout measures were calculated for the finite set fill slots as follows . fallout = Incorrect + spuriou s possible incorrec t", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REC", "sec_num": null }, { "text": "where \"possible incorrect\" is the number of possible incorrect answers which coul d be given in the response . The number of possible incorrect is not shown in the scor e report but a tally is kept internally by the scoring system . The method for keepin g this tally of possible incorrect has evolved during the course of the evaluation .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REC", "sec_num": null }, { "text": "In order to describe this evolution, a simple calculation of fallout for a singl e slot in a single template will be given .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "actua l", "sec_num": null }, { "text": "The instrument type slot has 16 possibl e fillers .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "actua l", "sec_num": null }, { "text": "If the key contains the filler GUN and the response contains the fille r GRENADE, then fallout would b e FAL = INC +SPU possible incorrec t 1 1 5 = 0 .0 7", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "actua l", "sec_num": null }, { "text": "The number of possible incorrect is the cardinality of the set of possibl e answers minus the number correct in the key which is 16 -1, or 15 .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "actua l", "sec_num": null }, { "text": "In phase one, the fallout measure assumed that the system was essentiall y choosing a subset of the finite set of possible fills when it gave a response . Fo r example, if the key for the instrument type slot contained GUN and GRENADE and th e response contained BOMB, GRENADE, and CUTTING DEVICE, the phase one fallout woul d be The number of possible incorrect was the cardinality of the set minus the tota l number of slot fills given in the key .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "actua l", "sec_num": null }, { "text": "During phase two, it was noticed that this simple approach to fallout was i n fact erroneous for several reasons . Some finite set slots allowed multiple uses of se t members due to cross-referencing requirements . For example, the slot fill CIVILIA N might be used multiple times in specifying the human target type for differen t human targets .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "actua l", "sec_num": null }, { "text": "Further complications arose when alternatives were given in the key for eac h such slot fill . In order to solve all of these problems, the calculation of the possibl e correct for the slot fills was revised to coincide more closely with the calculation use d in information retrieval .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "CIVILIAN : \"MARIO FLORES \" CIVILIAN : \"JOSE RODRIGUEZ \"", "sec_num": null }, { "text": "Each separate slot fill item is now thought of as bein g chosen from the entire finite set of possible fill items .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "CIVILIAN : \"MARIO FLORES \" CIVILIAN : \"JOSE RODRIGUEZ \"", "sec_num": null }, { "text": "In general, the number of possible incorrect is given by the followin g formula .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "CIVILIAN : \"MARIO FLORES \" CIVILIAN : \"JOSE RODRIGUEZ \"", "sec_num": null }, { "text": "(IUI -Ikeyvall ) keyva l where keyval stands for each of the key values including blanks, IUI is th e cardinality of the finite set U of possible slot fillers, and Ikeyvall is the number of key values corresponding to the response . If there are alternative key values for a response, then Ikeyvall > 1 . If the key is blank, then there are no corresponding key values and the contribution to the number of possible incorrect is the cardinality o f the finite set .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "E", "sec_num": null }, { "text": "Returning to our example of instrument types with the key containing GU N and GRENADE and the response containing BOMB, GRENADE, and CUTTING DEVICE , fallout will be recalculated using the new method of determining the possibl e incorrect . The number of possible incorrect is calculated by summing over the slo t fills . For GUN, the number of possible incorrect is the cardinality of the set, which i s 16, minus the number of slot fill alternatives given in the key, which in this case i s 1 . For GRENADE, the number of possible incorrect is also 15 . So the number o f possible incorrect for this slot is 15 + 15, or 30 . Since there is 1 incorrect and 1 spurious response, fallout is 2/30, or 7% . In phase one, fallout was 14% for this sam e example .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "E", "sec_num": null }, { "text": "If there are alternatives to a single slot fill in the key, the contribution to the number of possible incorrect by that slot fill is the cardinality of the finite set minu s the number of alternatives given . For example, if the key is GUN/GRENADE, th e number of possible incorrect is 16 -2, or 14 .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "E", "sec_num": null }, { "text": "If the key is blank, the number of possible incorrect is the cardinality of the finite set . For example, if the instrument type slot is blank in the key and th e response is GUN and GRENADE, then the fallout i s FAL = INC + SPU possible incorrec t 0 +2", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "E", "sec_num": null }, { "text": "1 6 2 1 6 = 0 .1 3", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "E", "sec_num": null }, { "text": "Notice that if the number of spurious responses is great enough, fallout can b e more than 100% .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "E", "sec_num": null }, { "text": "Recall is a measure of completeness in the sense that it measures the amount o f relevant data extracted relative to the total available . It is the true positive rate .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Meaning of Metric s", "sec_num": null }, { "text": "A mnemonic for recall can be constructed by imagining that you have been asked t o read the entire answer key, then fill in templates with all that you hav e \"remembered\" or \"recalled .\" Your score would be the total correctly recalled out o f the total possible .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Meaning of Metric s", "sec_num": null }, { "text": "Precision is the accuracy with which a system extracts data. It is the amoun t of relevant data relative to the total put in by the system . A mnemonic for precisio n is to imagine that each time a system fills a slot it is throwing a dart at a dartboard . All of the bull's-eyes are correct . Precision is a measure of the number of bull's-eye s relative to the number of darts thrown . Precision can also be described as th e tendency of a system to avoid assigning bad fillers as it assigns more good fillers .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Meaning of Metric s", "sec_num": null }, { "text": "Fallout is a measure of the false positive rate . It is the tendency of the syste m to assign incorrect fillers as the number of potential incorrect fillers increases . So , for a mnemonic, if you are imagining the dartboard again, fallout measures th e number of darts that \"fall outside\" of the bull's-eye relative to the size of the are a outside the bull's-eye .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Meaning of Metric s", "sec_num": null }, { "text": "Fallout can only be assigned for slots with a calculabl e number of possible incorrect .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Meaning of Metric s", "sec_num": null }, { "text": "Only some of the slots have a finite set of slot fill s associated with them .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Meaning of Metric s", "sec_num": null }, { "text": "The others have fills that come from potentially infinite set s and hence cannot be assigned a fallout score .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Meaning of Metric s", "sec_num": null }, { "text": "Overgeneration is a measure of spurious generation .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Meaning of Metric s", "sec_num": null }, { "text": "It is the amount o f spurious fillers assigned in relation to the total assigned . Overgeneration wa s calculated to deter overgeneration as an approach to higher scores . A mnemonic -fo r overgeneration can be constructed by imagining that required fills and extra fill s are in a box . Overgeneration is represented by the area that the extra fills take up i n relation to the total area .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Meaning of Metric s", "sec_num": null }, { "text": "The last four rows of the score report in Figure 1 are summary score rows . I n phase one, there was one summary score row that represented the totals of th e columns for the scoring categories including possible and actual . The metrics were then calculated based on those totals and appeared in the appropriate columns in th e lower righthand portion of the chart . The summary metrics are always calculate d from the items in the summary totals and are never the result of averaging th e metrics for the slots .", "cite_spans": [], "ref_spans": [ { "start": 42, "end": 50, "text": "Figure 1", "ref_id": null } ], "eq_spans": [], "section": "Summary Score s", "sec_num": null }, { "text": "In phase two, it was decided that the scoring system should keep the interna l tallies needed to supply several summary score rows, only one of which would be th e total of the slot scores shown in the columns of the score report . The scoring of slot s in the missing and spurious templates was the issue which gave rise to multipl e summary rows .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Summary Score s", "sec_num": null }, { "text": "In phase one, spurious templates were scored as spurious in th e template id slot only . The spurious slot fillers aside from the template id slot fille r were not scored as spurious . Missing templates, however, were scored in the templat e id slot and in the individual missing slots . This method of scoring did not penalize a s much for overpopulating the database as it did for underpopulating it .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Summary Score s", "sec_num": null }, { "text": "In phase two, we wanted to find out how the systems scored if overpopulatin g and underpopulating the database were treated equally . Two summary rows were added, one of which scored spurious and missing in the template id only and th e other of which scored spurious and missing templates for all of the spurious and missing slot fills . The official scores were still taken from the same summary row a s in phase one, but the other two rows were there for analysis .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Summary Score s", "sec_num": null }, { "text": "The global summary rows are listed on the score report in order of strictnes s based on the scoring of missing and spurious templates . The MATCHED ONLY row has missing and spurious templates only scored in the template id slot . This row contains the least strict of the scores for the system . The MATCHED/MISSING row contains the official test results . The missing template slots are scored as missing . The spuriou s templates are scored only in the template id slot . The totals in this row are the total s of the tallies in the columns as shown . The ALL TEMPLATES row has missing templat e slots scored as missing and spurious template slots scored as spurious . This ro w contains the strictest scores for the system . A fourth summary row was added to allow analysis of system performance o n only the set fill slots . The SET FILLS ONLY row contains totals for slots with finite se t fills only . A global fallout score is calculated for these slots and given in the fallou t column of this row .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Summary Score s", "sec_num": null } ], "back_matter": [ { "text": "The evaluation metrics for MUC-3 had utility for system development and fo r the reporting and analysis of the results of the evaluation . The metrics were adapte d from simpler task models and were still evolving when the evaluation wa s performed . There has been consistent agreement on the necessity of basi c measurements of completeness, accuracy, false alarm rate, and overgeneration . These measurements were accomplished through the metrics of recall, precision , fallout, and overgeneration as defined for MUC-3 .The global summary score s provide several different views of system performance . However, further analysis o f the current results is possible based on the information in the official score reports . The template by template scores are officially reported and can be used as a basis fo r further analysis .For example, performance at the message level can be calculate d from the template by template scores for the systems .While the metrics of recall, precision, fallout, and overgeneration have bee n defined for MUC-3, further research into the metrics and their implementation need s to be done . Additional measurements may be required . More refined definitions of the current measurements are probably needed . The complexities of optional fills , alternatives in the key, partial credit, and distribution of partial credit over ke y values, to name a few, still need to be examined more closely with consideration given to their effects on the metrics .These complexities have made it difficult t o fully test the scoring system software and require more attention to be paid t o detecting and isolating subtle errors .A different treatment of the slots will need to be attempted . For example, the template id slot is unique among the slots and will b e kept separate when the summary measures are calculated in the future .A singl e overall measure of performance may be possible in the future once the roles o f recall and precision are more fully determined . All of these avenues of furthe r research have been opened up by the definition of a set of metrics for MUC-3 and th e development of a scoring system embodying those metrics .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "CONCLUSIONS AND FURTHER RESEARC H", "sec_num": null }, { "text": "Many of the scoring issues were debated and resolved in consultation wit h members of the Program Committee . David Lewis provided technical guidance . Pet e Halverson developed the scoring system . The participants provided feedback . Beth Sundheim was a sounding board for many of the issues that arose during th e evolution of the MUC-3 scoring .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "ACKNOWLEDGEMENT S", "sec_num": null } ], "bib_entries": {}, "ref_entries": { "FIGREF0": { "num": null, "uris": null, "text": "Figure 2 : Scoring Categories", "type_str": "figure" } } } }