COfEE: A Comprehensive Ontology for Event Extraction from text

Balali, Ali; Asadpour, Masoud; Jafari, Seyed Hossein

doi:10.48550/arxiv.2107.10326

2021

DOI: 10.48550/arxiv.2107.10326

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COfEE: A Comprehensive Ontology for Event Extraction from text

Ali Balali¹,

Masoud Asadpour²,

Seyed Hossein Jafari³

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2024

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Cited by 2 publications

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“…If directly applied the existing extraction technologies to the judicial field, they will face the problem of incident type mismatch (Filtz et al, 2020;Li et al, 2020). In addition, many extraction technologies (e.g., Balali et al, 2021;Chen et al, 2015;Nguyen et al, 2016) were experimentally verified on publicly available English data sets, but in the Chinese judicial field, as far as we know, there was no standard experimental data (Feng et al, 2022). Furthermore, in Chinese divorce legal cases, there are many sentences containing multiple events that share arguments or trigger words, but most of the existing technologies are focused on extracting a single event from a single sentence (Zeng et al, 2018), which cannot solve this problem.…”

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confidence: 99%

Judicial intelligent assistant system: Extracting events from Chinese divorce cases to detect disputes for the judge

Zhang,

Li,

Sheng

et al. 2024

Expert Systems

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In the formal procedure of Chinese civil cases, the textual materials provided by different parties describe the development process of the cases. It is a difficult but necessary task to extract the key information for the cases from these textual materials and to clarify the dispute focus of related parties. Currently, officers read the materials manually and use methods, such as keyword searching and regular matching, to get the target information. These approaches are time‐consuming and heavily depend on prior knowledge and the carefulness of the officers. To assist the officers in enhancing working efficiency and accuracy, we conduct a case study of detecting disputes from Chinese divorce cases based on proposing a Two‐Round‐Labeling (TRL) event extracting technique in this article. We implement the Judicial Intelligent Assistant (JIA) system according to the proposed approach to (1) automatically extract focus events from divorce case materials, (2) align events by identifying co‐reference among them, and (3) detect conflicts among events brought by the plaintiff and the defendant. With the JIA system, it is convenient for judges to determine the disputed issues in Chinese divorce cases. Experimental results demonstrate that the proposed approach and system can obtain the focus of Chinese divorce cases and detect conflicts more effectively and efficiently compared with the existing method.

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confidence: 99%

Judicial intelligent assistant system: Extracting events from Chinese divorce cases to detect disputes for the judge

Zhang,

Li,

Sheng

et al. 2024

Expert Systems

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“…Other related datasets that insufficiently overlap ICBe's domain for comparison include BCOW(Leng and Singer, 1988),WEIS (McClelland, 1978), CREON(Hermann, 1984), CASCON(Bloomfield and Moulton., 1989), SHERFACS(Sherman, 2000), Real-Time Phoenix(Brandt et al, 2018), and COfEE(Balali et al, 2021) (see histories inMerritt, 1994 andHall, 2006).4 See Balali et al (2021) for a recent review of ontological depth and availability of Gold Standard example text.…”

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confidence: 99%

Introducing ICBe: an event extraction dataset from narratives about international crises

Douglass,

Scherer,

Gannon

et al. 2024

PSRM

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How do international crises unfold? We conceptualize international relations as a strategic chess game between adversaries and develop a systematic way to measure pieces, moves, and gambits accurately and consistently over a hundred years of history. We introduce a new ontology and dataset of international events called ICBe based on a very high-quality corpus of narratives from the International Crisis Behavior (ICB) Project. We demonstrate that ICBe has higher coverage, recall, and precision than existing state of the art datasets and conduct two detailed case studies of the Cuban Missile Crisis (1962) and the Crimea-Donbas Crisis (2014). We further introduce two new event visualizations (event iconography and crisis maps), an automated benchmark for measuring event recall using natural language processing (synthetic narratives), and an ontology reconstruction task for objectively measuring event precision. We make the data, supplementary appendix, replication material, and visualizations of every historical episode available at a companion website crisisevents.org.

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COfEE: A Comprehensive Ontology for Event Extraction from text

Cited by 2 publications

References 0 publications

Judicial intelligent assistant system: Extracting events from Chinese divorce cases to detect disputes for the judge

Judicial intelligent assistant system: Extracting events from Chinese divorce cases to detect disputes for the judge

Introducing ICBe: an event extraction dataset from narratives about international crises

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