Building referring expression corpora with and without feedback.
The design of data collection experiments involving human participants is a common task in Referring Expression Generation (REG) and related fields. Many (or most) REG data collection tasks are implemented by making use of a human–computer (e.g., web-based) communicative setting, in which participan...
| Publicado en: | Language Resources & Evaluation Vol. 54; no. 4; pp. 875 - 892 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Dec2020
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=146751853&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 146751853 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Dec2020 vid: 54 iid: 4 pid: 237 pub: Springer Nature artinfo: ui: 146751853 10.1007/s10579-020-09497-2 ppf: 875 ppct: 17 formats: fmt: @attributes: type: P size: 1.1MB tig: atl: Building referring expression corpora with and without feedback. aug: au: da Silva Rocha, Danillo Paraboni, Ivandré affil: School of Arts, Sciences and Humanities (EACH), University of São Paulo (USP), São Paulo, Brazil su: Corpora Acquisition of data Perimetry Natural languages sug: subj: Corpora Acquisition of data Perimetry Natural languages keyword: Natural Language Generation Reference production Referring Expression Generation ab: The design of data collection experiments involving human participants is a common task in Referring Expression Generation (REG) and related fields. Many (or most) REG data collection tasks are implemented by making use of a human–computer (e.g., web-based) communicative setting, in which participants do not have any particular addressee in mind and do not receive any feedback regarding the appropriateness (e.g., uniqueness) of the descriptions that they produce. Others, at a possibly higher cost, make use of participant pairs engaged in some form of dialogue in which hearers may provide feedback allowing speakers to rephrase ambiguous or otherwise ill-formed descriptions. Leaving the issue of cost aside, however, it remains unclear whether the two methods elicit similar referring expressions for the purpose of REG research. To shed light on this issue, this paper presents a REG corpus built under three experimental conditions: a standard human–computer (or web-based) setting in which no feedback is available to the speaker, and two settings in which feedback regarding the appropriateness of the description may be provided either by an automated parsing tool or by a second participant at the receiving end of the communication. The corpus contains fully annotated descriptions in two domains—simple geometric objects and realistic human face images—and it is provided as a resource for the training and testing of REG algorithms in these communicative settings. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2020. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2020 holdings: @attributes: islocal: N |
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