Tamil is a morphologically rich language with agglutinative nature. Being agglutinative language most of the word features are postpositionally affixed to the root word. The morphological generator takes lemma, POS category and morpho-lexical description as input and gives a word-form as output. It is a reverse process of morphological analyzer. In any natural language generation system, morpho...

This work investigates the role of semantic clause types and modality in argumentative texts. We annotate argumentative microtexts with Situation Entity (SE) classes and additionately label the segments that contain modal verbs with their modal senses. We analyse both the correlation of SE classes and of modal verbs and senses with components of argument structures (such as premises and conclus...

本論文合併兩種方法預測未知動詞的詞類。第一種方法為規則法,即從訓練 語料中歸納出未知動詞組成的構詞規律,分成兩個主要的判斷方式:一、依 照未知動詞的組成的關鍵字決定其分類。二、依照未知動詞的構成組合決定 其分類。 關鍵字法首先將動詞依長度分為四組。第一組為二字詞、三字詞、四字詞、 五字以上的詞彙。在對實際語料的觀察下,發現不同詞長的動詞結構相異, 因此將語料依詞長分組。例如:三字詞可訓練出「好」、「出」兩條規則決 定動詞的詞類,其他長度的未知動詞並沒有這兩條規則,另外「化」規則不 適用於二字動詞。 規則法的第二部分為依照構成組合決定其分類。在觀察未知動詞時,發現有 部分未知動詞的組合很具有規律,我們就將訓練語料中未知動詞的組合做個 歸納,得到九種組合。在十次實驗中,規則法可以處理的未知動詞平均約為 23.19%,猜測正確的比例為 91.67%。 二、相似法為利用與未知動詞相似的例子來...

Verb aspect is a grammatical and lexical category that encodes temporal unfolding and duration of events described by verbs. It is a potentially interesting source of information for various computational tasks, but has so far not been studied in much depth from the perspective of automatic processing. Slavic languages are particularly interesting in this respect, as they encode aspect through ...

We report of a rule based, knowledge-base driven tool to automatically classify Hindi verbs in syntactic perspective. We also report of developing the largest lexical resource for Hindi verbs along with the information on their class based on valency and some syntactic diagnostic tests as well as their morphological/inflectional type. We use this resource to develop the tool to automatically cl...

The event structure (aktionsart) is a widely discussed issue for the representation of verbal semantics in languages. However, there is still problems for the classification of verbs into state, activity, accomplishment, achievement and semelfactive. It is also not clear where are the differences of them embedded in terms of lexical, semantic or syntactic levels. In this paper, we will give a d...

This paper examines the collocational patterns of Mandarin verbs of conversation and proposes that a finer classification scheme than the flat structure of ‘frames’ [cf. Fillmore and Atkins 1992; Baker et al. 2003] is needed to capture the semantic granularity of verb types. The notion of a ‘subframe’ is introduced and utilized to explain the syntactic-semantic interdependencies among different...

This short paper is focused on the formal semantic model: Universal Semantic Code (USC), which acquires a semantic lexicon from thesauruses and pairs it with formal meaning representation. The USC model postulates: Knowledge Inference (KI) is effective only on the basis of Semantic Knowledge Representation (SKR). The USC model represents formalized meanings of verbs and phrasal verbs as a main ...

Data mining allows the exploration of sequences of phenomena, whereas one usually tends to focus on isolated phenomena or on the relation between two phenomena. It offers invaluable tools for theoretical analyses and exploration of the structure of sentences, texts, dialogues, and speech. We report here the results of an attempt at using it for inspecting sequences of verbs from French accounts...

Support Vector Machines have been applied to text classification with great success. In this paper, we apply and evaluate the impact of using part-ofspeech tags (nouns, proper nouns, adjectives and verbs) as a feature selection procedure in a European Portuguese written dataset – the Portuguese Attorney General’s Office documents. From the results, we can conclude that verbs alone don’t have en...