Using Bilingual Patents for Translation Training

Proceedings of the 28th International Conference on Computational Linguistics, pages 339–349 Barcelona, Spain (Online), December 8-13, 2020 339 CEREC: A Corpus for Entity Resolution in Email Conversations Parag Pravin Dakle Department of Computer Science The University of Texas at Dallas paragpravin.dakle@utdallas.edu Dan I. Moldovan Department of Computer Science The University of Texas at Dallas moldovan@utdallas.edu Abstract We present the first large scale corpus for entity resolution in email conversations (CEREC). The corpus consists of 6001 email threads from the Enron Email Corpus containing 36,448 email messages and 38,996 entity coreference chains. The annotation is carried out as a two-step process with minimal manual effort. Experiments are carried out for evaluating different features and performance of four baselines on the created corpus. For the task of mention identification and coreference resolution, a best performance of 54.1 F1 is reported, highlighting the room for improvement. An in-depth qualitative and quantitative error analysis is presented to understand the limitations of the baselines considered. 1 Introduction Entity resolution is defined as linking referring spans of text that point to the same discourse entity by CoNLL 2012 (Pradhan et al., 2012) and MUC (Grishman and Sundheim, 1996) shared tasks. The corpora used for this task primarily consist of text from news (Pradhan et al., 2012; Cybulska and Vossen, 2014; Recasens et al., 2010; Grishman and Sundheim, 1996), web-logs and transcripted dialogs. This research focusses on the entity resolution task for email conversations. Example 1 shows a sample email message and the corresponding entities. The boldfaced tokens represent entities and the numbers beside them represent coreference chain identifiers. An Entity is defined as an object or a group of objects in the real world and a span of text referring to an entity is called a Mention. When all mentions in a text which refer to the same real-world entity are linked together, they form a coreference chain. Example 1. Example of entity resolution task in email conversations Date: Mon, 17 Dec 2001 14:28:03 -0800 (PST) From: g..barkowsky@enron.com(1) To: theresa.staab@enron.com(2) Subject: RE: Final Statements and Invoices for November X-From: Barkowsky, Gloria G.(1) X-To: Staab, Theresa(2) yes, I(1) ’ll do this. Do you(2) have anything for Crestone and Lost Creek(3)? Dakle et al. (2020) first studied entity resolution in email conversations using a small annotated cor- pus. Following the same task definition, this paper builds on their work and makes the following key contributions: 1. A large corpus for entity resolution in email conversations (CEREC), weakly annotated for mentions and coreference chains, is presented. Detailed corpus statistics are also discussed. The corpus will be released along with the paper1. This work is licensed under a Creative Commons Attribution 4.0 International License. License details: http:// creativecommons.org/licenses/by/4.0/. 1https://github.com/paragdakle/emailcoref 340 2. Experiments with several baseline models are carried out and their results are reported. A qualitative and quantitative error analysis of the results is presented. The paper is organized as follows: Section 2 reviews related work done on email processing and corpora for emails and entity resolution. Section 3 describes …

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