Entity Mention

From GM-RKB
(Redirected from Textual Entity Referencer)
Jump to navigation Jump to search

An entity mention is a referring expression that is an entity referencer (whose referent is an entity).



References

2011

2009

  • WordNet.
    • mention: make reference to.
    • en.wiktionary.org/wiki/mention
    • mention: A speaking or notice of anything, usually in a brief or cursory manner. Used especially in the phrase to make mention of; To speak of something
  • (Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/Referring_expression
    • A referring expression (RE), in linguistics, is any noun phrase, or surrogate for a noun phrase, whose function in a text (spoken, signed or written on a particular occasion) is to "pick out" an individual person, place, object, or a set of persons, places, objects, etc. The technical terminology for "pick out" differs a great deal from one school of linguistics to another. The most widespread term is probably refer, and a thing "picked out" is a referent, as for example in the work of John Lyons. In linguistics, the study of reference belongs to pragmatics, the study of language use, though it is also a matter of great interest to philosophers, especially those wishing to understand the nature of knowledge, perception and cognition more generally.
    • The kinds of expressions which can refer (as so defined) are:
      • (1) a noun phrase of any structure, such as: the taxi in The taxi's waiting outside; the apple on the table in Bring me the apple on the table; and those five boys in Those five boys were off school last week. In those languages which, like English, encode definiteness, REs are typically marked for definiteness. In the examples given, this is done by the definite article the or the demonstrative adjective, here those.
      • (2) a noun-phrase surrogate, i.e. a pronoun, such as it in It's waiting outside and Bring me it; and they in They were off school last week. The referent of such a pronoun may vary according to context - e.g. the referent of me depends on who the speaker is - and this property is technically an instance of deixis.
      • (3) a proper name, like Sarah, London, The Eiffel Tower, or The Beatles. The intimate link between proper names and type (1) REs is shown by the definite article that appears in many of them. In many languages this happens far more consistently than in English. Proper names are often taken to refer, in principle, to the same referent independently of the context in which the name is used and in all possible worlds, i.e. they are in Saul Kripke's terminology rigid designators.
  • (Kulkarni et al., 2009) ⇒ Sayali Kulkarni, Amit Singh, Ganesh Ramakrishnan, Soumen Chakrabarti. (2009). “Collective Annotation of Wikipedia Entities in Web Text.” In: Proceedings of ACM SIGKDD Conference (KDD-2009). doi:10.1145/1557019.1557073.
    • To take the first step beyond keyword-based search toward entity-based search, suitable token spans ("spots") on documents must be identified as references to real-world entities from an entity catalog.

2008

  • (Sarawagi, 2008) ⇒ Sunita Sarawagi. (2008). “Information extraction.” In: FnT Databases, 1(3).
  • (Ding et al., 2008) ⇒ Xiaowen Ding, Bing Liu, and Philip S. Yu. (2008). “A Holistic Lexicon-based Approach to Opinion Mining.” In: Proceedings of the International Conference on Web Search and Web Data Mining (WSDM 2008).
    • Definition (object): An object $O$ is an entity which can be a product, person, event, organization, or topic. It is associated with a pair, O: (T, A), where [math]\displaystyle{ T }[/math] is a hierarchy or taxonomy of components (or parts), sub-components, and so on, and [math]\displaystyle{ A }[/math] is a set of attributes of O. Each component has its own set of subcomponents and attributes.

      Example 1: A particular brand of digital camera is an object. It has a set of components, e.g., lens, battery, etc., and also a set of attributes, e.g., picture quality, size, etc. The battery component also has its set of attributes, e.g., battery life, battery size, etc. Essentially, an object is represented as a tree. The root is the object itself. Each non-root node is a component or subcomponent of the object. Each link is a part-of relationship. Each node is also associated with a set of attributes. An opinion can be expressed on any node and any attribute of the node.

      Example 2: Following Example 1, one can express an opinion on the camera (the root node), e.g., “I do not like this camera”, or on one of its attributes, e.g., “the picture quality of this camera is poor”. Likewise, one can also express an opinion on any one of the camera’s components or the attribute of the component.

      To simplify our discussion, we use the word “features” to represent both components and attributes, which allows us to omit the hierarchy. Using features for products is also quite common in practice. For an ordinary user, it is probably too complex to use a hierarchical representation of features and opinions. We note that in this framework the object itself is also treated as a feature.

      Let the review be r. In the most general case, r consists of a sequence of sentences r = <s1, s2, …, sm>.

    • Definition (explicit and implicit feature):
      • If a feature f appears in review r, it is called an explicit feature in r. If f does not appear in r but is implied, it is called an implicit feature in r.
    • Example 3: “battery life” in the following sentence is an explicit feature:
      • “The battery life of this camera is too short”.
    • “Size” is an implicit feature in the following sentence as it does not appear in the sentence but it is implied:
      • “This camera is too large”.
    • Here, “large” is called a feature indicator.

2002

1982