태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Morphological Analysis is a central task in language processing that can take a word as input and detect the various morphological entities in the word and provide a morphological representation of it.
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
CELEX database comprises three different searchable lexical databases, Dutch, English and German. The lexical data contained in each database is divided into five categories: orthography, phonology, morphology, syntax (word class) and word frequency. Source: Polysemy and Brevity versus Frequency in Language Image Source: https://www.aclweb.org/anthology/W17-7619.pdf
Polyglot-NER builds massive multilingual annotators with minimal human expertise and intervention. Source: POLYGLOT-NER: Massive Multilingual Named Entity Recognition
Wikipedia Title is a dataset for learning character-level compositionality from the character visual characteristics. It consists of a collection of Wikipedia titles in Chinese, Japanese or Korean labelled with the category to which the article belongs. Source: https://arxiv.org/abs/1704.04859
Contains 350 tweets with more than 8,000 words including 3,000 unique words written in Egyptian dialect. The tweets have much dialectal content covering most of dialectal Egyptian phonological, morphological, and syntactic phenomena. It also includes Twitter-specific aspects of the text, such as #hashtags, @mentions, emoticons and URLs. Source: A Neural Architecture for Dialectal Arabic Segmentation
A new high accuracy Turkish morphology dataset. Source: Morphological analysis using a sequence decoder
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.