ETER: a New Metric for the Evaluation of Hierarchical Named Entity Recognition

• Main Authors: Ben Jannet, Mohamed, Adda-Decker, Martine, Galibert, Olivier, Kahn, Juliette, Rosset, Sophie
• Other Authors: LPP - Laboratoire de Phonétique et Phonologie - UMR 7018 (LPP), Université Sorbonne Nouvelle - Paris 3-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI), Université Paris-Sud - Paris 11 (UP11)-Sorbonne Université - UFR d'Ingénierie (UFR 919), Sorbonne Université (SU)-Sorbonne Université (SU)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris Saclay (COmUE), LNE, Université Paris-Sud - Paris 11 (UP11), This work was partially funded by the CIFRE convention 2012/0771, European Language Resources Association (ELRA), Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperi, ANR-11-IDEX-0005,USPC,Université Sorbonne Paris Cité(2011), ANR-12-BS02-0006,VERA,Analyse d'erreurs avancée pour la reconnaissance de la parole(2012)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2014
• Subjects: hierarchical named entity; metrics; evaluation; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; The Slot; Iceland
• Online Access: https://hal.science/hal-01134713

International audience This paper addresses the question of hierarchical named entity evaluation. In particular, we focus on metrics to deal with complex named entity structures as those introduced within the QUAERO project. The intended goal is to propose a smart way of evaluating partially correctly detected complex entities, beyond the scope of traditional metrics. None of the existing metrics are fully adequate to evaluate the proposed QUAERO task involving entity detection, classification and decomposition.We are discussing the strong and weak points of the existing metrics. We then introduce a new metric, the Entity Tree Error Rate (ETER), to evaluate hierarchical and structured named entity detection, classification and decomposition. The ETER metric builds upon the commonly accepted SER metric, but it takes the complex entity structure into account by measuring errors not only at the slot (or complex entity) level but also at a basic (atomic) entity level. We are comparing our new metric to the standard one using first some examples and then a set of real data selected from the ETAPE evaluation results.