This paper describes the SemEval 2018 Task 10 on Capturing Discriminative Attributes. Participants were asked to identify whether an attribute could help discriminate between two concepts. For example, a successful system should determine that urine is a discriminating feature in the word pair kidney,bone. The aim of the task is to better evaluate the capabili- ties of state of the art semantic models, beyond pure semantic similarity. The task attracted submissions from 21 teams, and the best sys- tem achieved a 0.75 F1 score.
SemEval-2018 Task 10: Capturing Discriminative Attributes
Alessandro LenciSecondo
;
2018-01-01
Abstract
This paper describes the SemEval 2018 Task 10 on Capturing Discriminative Attributes. Participants were asked to identify whether an attribute could help discriminate between two concepts. For example, a successful system should determine that urine is a discriminating feature in the word pair kidney,bone. The aim of the task is to better evaluate the capabili- ties of state of the art semantic models, beyond pure semantic similarity. The task attracted submissions from 21 teams, and the best sys- tem achieved a 0.75 F1 score.File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
Krebs_etal_2018.pdf
solo utenti autorizzati
Descrizione: Articolo principale
Tipologia:
Versione finale editoriale
Licenza:
NON PUBBLICO - accesso privato/ristretto
Dimensione
148.5 kB
Formato
Adobe PDF
|
148.5 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
