• Related term. A term that is semantically related to another term. In thesauri are related terms often coded RT and used for other kinds of semantic relations than synonymity (USE; UF), homonymity (separated by paranthetical qualifier), generic relations and partitative relations (BT; NT). Related terms may, for example express antagonistic relations, active/passive relations, causal relations, locative relations, paradigmatic relations.
• Synonymy (A denotes the same as B; A is equivalent with B).
• Temporal relation: A semantic relation in which a concept indicates a time or period of an event designated by another concept. Example: Second World War, 1939-1945.
• Troponymy is defined in WordNet 2 as: the semantic relation of being a manner of does something (or sense 2: “the place names of a region or a language considered collectively”).
How many kinds of semantic relations exist?
Is the number of semantic relations finite or infinite? What determines this number? In the quotation below (Rosario & Hearst, 2001) it is stated that there are contradictory views in theoretical linguistics regarding the semantic properties of noun compounds (NCs). Some argues that there exists a small set of semantic relationships that NCs may imply. Others argue that the semantics of NCs cannot be exhausted by any finite listing of relationships. Green (2001, P. 5-6) argues that the inventory of semantic relationships includes both a closed set of relationships (including mainly hierarchical and equivalence relationships) and an open set of relationships. Every time a new verb is coined, for example, the potential for the introduction of a new conceptual relationship arises.
The answer is probably that any relation between objects (or processes or anything else) may be reflected in languages between the corresponding concepts. “Love” is a relation between some people, e.g. Tom and Clare. ‘Tom’ and ‘Clare’ are thus (individual) concepts with the semantic relation ‘love’.
In addition to relations in the world, semantic relations may reflect relations in language including relations between objects and their symbols (as in synonyms). The limit to the number of semantic relations seems to be relations that nobody have found interesting to conceptualize. Different domains develop continuously new kinds of semantic relations. Rosario & Hearst (2001) thus identified 38 semantic relations within medicine.
In this work we aim for a representation that is intermediate in generality between standard case roles (such as Agent, Patient, Topic, Instrument), and the specificity required for information extraction. We have created a set of relations that are sufficiently general to cover a significant number of noun compounds, but that can be domain specific enough to be useful in analysis. We want to support relationships between entities that are shown to be important in cognitive linguistics, in particular we intend to support the kinds of inferences that arise from Talmy’s force dynamics (Talmy, 1985). It has been shown that relations of this kind can be combined in order to determine the “directionality” of a sentence (e.g., whether or not a politician is in favor of, or opposed to, a proposal) (Hearst, 1990). In the medical domain this translates to, for example, mapping a sentence into a representation showing that a chemical removes an entity that is blocking the passage of a fluid through a channel. The problem remains of determining what the appropriate kinds of relations are. In theoretical linguistics, there are contradictory views regarding the semantic properties of noun compounds (NCs). Levi (1978) argues that there exists a small set of semantic relationships that NCs may imply. Downing (1977) argues that the semantics of NCs cannot be exhausted by any finite listing of relationships. Between these two extremes lies Warren’s (1978) taxonomy of six major semantic relations organized into a hierarchical structure.
We have identified the 38 relations shown in Table 1 [omitted here]. We tried to produce relations that correspond to the linguistic theories such as those of Levi and Warren, but in many cases these are inappropriate. Levi’s classes are too general for our purposes; for example, she collapses the “location” and “time” relationships into one single class “In” and therefore field mouse and autumnal rain belong to the same class. Warren’s classification schema is much more detailed, and there is some overlap between the top levels of Warren’s hierarchy and our set of relations.” (Rosario & Hearst, 2001).
The most commonly used semantic relations have resemblance with lists of categories, for example, with Aristotle’s famous 10 categories:
3. Qualification (quality)
4. A relative (relation)
5. Where (place)
6. When (time)
7. Being-in-a-position (position)
8. Having (state)
9. Doing, (action)
10. Being-affected (affection)
They have also resemblance with commonly used grammatical categories. Such categories and grammatical relations represent abstractions or generalizations. The former example “love” may thus be seen as a special case of “being affected”. Although the number of semantic relations appears to be unlimited, in most cases a limited number of generalized kinds are used in practice.
How are semantic relations determined? (What are their “warrants”)?
Hjørland (2007) discusses the following possibilities:
a) Query/situation specific or idiosyncratic
b) Universal, Platonic entities/relations
c) “Deep semantics” common to all languages (or inherent in cognitive structures)
d) Specific to specific empirical languages (e.g. Swedish)
e) Domain or discourse specific
f) Other (e.g. determined by a company or by a workgroup, “user oriented”)
In information retrieval the basic functions for semantic relations may be conceived as contributing to the increase of recall and precision. The inclusion of synonyms and broader terms in a query may, for example, contribute to increased recall. The differentiation of homonyms and the specification of terms may increase precision. In this way may the widely use of standard semantic relations used in thesauri be explained functionally. There are, however, recommendations that the number of relations should be expanded:
“The participants [in a NISO 1999 workshop on standards for electronic thesauri] recommended that a much richer, hierarchically organized, set of relationships be developed. . . . There is reason to expect that provision for semantic relations in controlled vocabularies will become much more extensive in a future standard . . .” (Milstead, 2001,P. 65. (
How should we explain this demand for a much richer set of relationships than ordinarily used in, for example, thesauri? The answer may imply a criticism of the traditional recall/precision way of understanding information retrieval. What information searchers need are maps that inform them about the world (and the literature about that world) in which they live and act. They need such maps in order to formulate questions in the first hand. In order to formulate queries and to interact with information sources are advanced semantic tools often very useful. This is probably especially so in the humanities, where concepts are more clearly associated with world views. In Germany the concept of conceptual history (“Begriffsgeschichte”) is an illustration of this point: Historians and other humanist researchers have realized that in order to use sources from a given period, you have to know what the terms meant at the time. Therefore they have developed impressive historical dictionaries which provide detailed information about conceptual developments within different domains just as they have developed methodological principles on how to work with historical information sources (Hampsher-Monk; Tilmans&Vree, 1998).
An example of a semantic tool developed in
this tradition is Reallexikon der deutschenLiteraturwissenschaft (Weimar, 1997-2003), which provide the following information for each term:
• The term (e.g. ‘Bibliography’)
• A definition (e.g. Definition of ‘bibliography’)
• A history of the word (its etymology, e.g. The etymology of the word ‘bibliography’)
• A history of the concept. (E.g. the history of the meanings of ‘bibliography’)
• A history of the field (e.g. The history of bibliographies themselves) and
• A history of research about the field (e.g. The history of research on bibliographies, i.e. library science)
This example is mentioned because it illustrates the existence of important work which may inspire LIS to a broader approach to semantic relations. Not much research has investigated whether different domains need different kinds of semantic tools displaying different kinds of semantic relations. Roberts (1985) is an exception arguing for the importance for specific kinds of relations in the social sciences. Hjørland (2004) argued that “traditional standardized and universal tools like thesauri may perhaps be better suited for technological fields, while historical dictionaries in the tradition of Begriffsgeschichte may be better suited for the humanities.
Cross-language cognates (words with similar form and meaning in different languages) are of special interest for designing a model of the bilingual lexicon because there is a possibility that they may have overlapping representations between the two languages of a bilingual. Among other effects related to cognates, the cognate facilitation effect was discovered: bilinguals produce and recognize cognates faster than non-cognates. One possibility to explain the cognate facilitation effect is through shared/overlapping representations of cognates and the word frequency effect. Since using a pair of cognates in two languages requires accessing (almost) the same phonological form in connection to (almost) the same concept, the overall frequency of a cognate increases.
Research in first-language reading has repeatedly documented a strong correlational relationshipbetween students’ vocabulary knowledge and their ability to comprehend text (Anderson & Freebody,1981).
Research in second-language reading has tended to focus more on morphology and syntax than onvocabulary (Weber, 1991).
One of the underlying assumptions in bilingual education is that students who are literate in their firstlanguage can transfer some of their knowledge and skills in first-language reading to second-languagereading (Grabe, 1988). There is some empirical evidence for this claim (Hudelson, 1981;Langer, Bartolom6, Vasquez, & Lucas, 1990). For example, we know that students’ readingperformance in their first language tends to correlate with that in their second language (Tregar&Wong, 1984), and that proficient readers in both languages, as compared to less proficient readers, arebetter at using “meaning making” strategies in the two languages (Langer et al., 1990). However, wedo not know much about the specific types of knowledge and strategies that transfer, nor do we knowthe conditions under which such transference might occur.
The purpose of our study was to examine the extent to which bilingual Persian students in the intermediate grades in Iran are able to transfer vocabulary knowledge in their first languageto reading in their second language through the use of cognates. Many words in English, especially inacademic and technical English, have close Iranian cognates. That is, Persian words with obviousorthographic similarity and closely related meanings. In many cases, words in the two languages arealmost identical both in spelling and meaning (e.g., balcony, and buss, mother). Sometimes there are onlyminor, predictable changes in spelling (e.g., orange/نارنج, paradise/پردیس, and damp/دم).Because much of English academic vocabulary is derived from Latin, many words that are academic orrare words in English have cognates that
تحقیقات گذشته نشان داده اند که تلاش های بازاریابی می تواند به طور کارآمدتری در سرتاسر کانال ها تخصیص یابد،با این وجود دانش ما در مورد این مسئله محدود است (نسلاین و شنکر 4،2006).در مورد بیشتر بخوانید...