Corpus Annotation Tool

RYCHLÝ, Pavel. Corpus Annotation Tool. 2017.

Základní údaje

• Originální název: Corpus Annotation Tool
• Autoři: RYCHLÝ, Pavel (203 Česká republika, garant, domácí).
• Vydání: 2017.

Další údaje

• Originální jazyk: angličtina
• Typ výsledku: Software
• Obor: 60200 6.2 Languages and Literature
• Stát vydavatele: Česká republika
• Utajení: není předmětem státního či obchodního tajemství
• WWW: URL
• Kód RIV: RIV/00216224:14330/17:00096859
• Organizační jednotka: Fakulta informatiky
• Klíčová slova anglicky: text corpora; corpus annotation; part of speech tagging
• Technické parametry: The tool was used to annotate texts in 6 languages by 16 annotators in total. Czech and Norwegian corpora were annotated mainly for evaluation reasons, there are several PoS annotated (including UD tag set) corpora for both languages. Annotation of 4 Ethiopian languages (Amharic, Oromo, Somali, Tigrinya) was used to build respective PoS taggers which are part of the HaBiT system.

Anotace

The main goal of this work is an annotation tool for easy and fast production of small annotated corpora for languages without linguistics resources. The tool is optimised for the following priorities: Simple tool for instant usage: The client part of the tool is a web application which works in any browser, it requires small amount of all resources (memory, internet connection, screen size), it could be used even from mobile devices (tablets, phones). Using small standard tag set: If possible, we have used Universal Dependencies (UD) tag set (version 2). It is well documented and used for many different languages. The main description of the tags is directly included in the tool with links to the UD site. Fast navigation: Users can use mouse or keyboard for navigation, only one or two mouse clicks or key strokes are needed for annotation of one token. All sentences are pre-annotated via an builtin adaptive tagger and only incorrect annotation have to be corrected by users. Clean texts: Users can (and are instructed to) reject to annotate a sentence if the sentence is not clear.

Návaznosti

• 7F14047, projekt VaV: Název: Harvesting big text data for under-resourced languages (Akronym: HaBiT)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Harvesting big text data for under-resourced languages