such features include sense, register, do- main spccilicity, pragmatic restrictions on usage, scnlan- lic markcdncss, and orientation, as well as automatically ictcnlifiecl links between words (e.g., semantic rclalcd- hess, syllollynly, antonylny, and tneronymy). aulomal- ically learning features of this type from hugc corpora allows the construction or augmentation of lexicons, and the assignment of scmanlic htbcls lo words and phrases in running text. this information in turn can bc used to help dcterlninc addilional features at the it?teal, clause, sentence, or document level. tiffs paper explores lira benelits that some lexical fea- tures of adjectives offer lor the prediction of a contexlual sentence-level feature, suojectivity. subjectivity in nat- ural language re[crs to aspects of language used to ex- press opinions and ewfluations. the computatiomtl task addressed here is to distinguish sentences used to present opinions and other tbrms of subjectivity (suojective sen- tences, e.g., "at several different layers, its a fascinating title") from sentences used to objectively present factual information (objective sentences, e.g., "bell industries inc. increased its quarterly to 10 cents from 7 cents a share"). much research in discourse processing has focused on task-oriented and insmmtional dialogs. the task ad- dressed here comes to the fore in other genres, especially news reporting and lnternet lorums, in which opinions of various agents are expressed and where subjectivity judgements couht help in recognizing inllammatory rues- sages ("llanles) and mining online sources for product reviews. ()thor (asks for whicll subjectivity recognition is potentially very useful include infornmtion extraction and information retrieval. assigning sub.icctivity labels to documents or portions of documents is an example of non-topical characteri?ation f information. current in- formation extraction and rolricval lechnology focuses al- most exclusively on lhe subject matter of the documcnls. yet, additiomtl components of a document inllucncc its relevance to imrlicuhu ? users or tasks, including, for ex- alnple, the evidential slatus el: lhc material presented, and attitudes adopted in fawn" or against a lmrticular person, event, or posilion (e.g., articles on a presidenlial cam- paign wrillen to promote a specific candidate). in sum- marization, subjectivity judgmcnls could be included in documcllt proiilcs to augment aulomatically produced docunacnt summaries, and to hel l) the user make rele- vance judgments when using a search engine. ()thor work on sub.iectivity (wicbc et al., 1999; bruce and wicbc, 2000) has established a positive and statisti- cally signilicant correlation with the presence of adiec- lives.effects of adjective orientation and gradability on sentence subjectivity vas i le ios  hatz ivass i log lou depar tment  o1 computer  sc ience co lumbia  un ivers i l y new york,  ny  10027 vh@cs ,  co lumbia ,  edu janyce  m.  wiebe depar tment  o f  computer  sc ience new mex ico  state un ivers i ty las  cruces ,  nm 88003 w iebe@cs ,  nmsu.