Jump to content

Referring expression generation

Add links
From Wikipedia, the free encyclopedia
This is an old revision of this page, as edited by THuppke (talk | contribs) at 14:36, 15 September 2015 (Extending the article: Extending the History paragraph). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

Referring expression generation is a subtask of Natural language generation (NLG), which involves creating referring expressions (noun phrases) that identify specific entities to the reader. A variety of algorithms have been developed in the NLG community to generate different types of referring expressions.

History

REG goes back to the early days of NLG. One of the first approaches was done by Winograd[1] in 1972 who developed an "incremental" REG algorithm for his SHRDLU program. Afterwards researchers started to model the human abilities to create referring expressions in the 1980s. This new approach to the topic was influenced by the researchers Appelt and Kronfeld who created the programs KAMP and BERTRAND[2][3][4] and considered referring expressions as parts of bigger speech acts. [5]

Some of their most interesting findings were the fact that referring expressions can be used to add information beyond the identification of the referent[3] as well as the influence of communicative context and the Gricean maxims on referring expressions.[2] Furthermore its skepticism concerning the naturalness of minimal descriptions made Appelt and Kronfeld's research a foundation of later work on REG. [5]

The search for simple, well-defined problems changed the direction of research in the early 1990s. This new approach was lead by Dale and Reiter who stressed the identification of the referent as the central goal.[6][7][8][9] Like Appelt[2] they discuss the connection between the Gricean maxims and referring expressions in their culminant paper[10] in which they also propose a formal Problem Definition. Furthermore Reiter and Dale discuss the Full Brevity and Greedy Heuristics algorithms as well as their Incremental Algorithm(IA) which became one of the most important algorithms in REG. [5]

After 2000 the research began to lift some of the simplifying assumptions, that had been made in early REG research in order to create more simple algorithms. Different research groups concentrated on different limitations creating several expanded algorithms. Often these extend the IA in a single perspective for example in relation to:

  • Reference to Sets
  • Relational Descriptions
  • Context Dependency
  • Vagueness
  • Gradability
  • Salience
  • Generation of Pronouns

Many simplifying assumptions are still in place or have just begun to be worked on. Also a combination of the different extensions has yet to be done and is called a "non-trivial enterprise" by Krahmer and van Deemter. [5]

Example

For example, the following text has several referring expressions

He told the tourist that rain was expected tonight in Southern Scotland.

  • He is a pronoun which refers to a person who was previously mentioned in the conversation.
  • the tourist is a definite noun phrase which identifies another person
  • tonight is a temporal referent which identifies a particular time period
  • Southern Scotland is a spatial reference which identifies a particular spatial region

Criteria for good referents

Ideally, a good referring expression should satisfy a number of criteria:

  • Referential success: It should unambiguously identify the referent to the reader.
  • Ease of comprehension: The reader should be able to quickly read and understand it.
  • Computational complexity: The generation algorithm should be fast
  • No false inferences: The expression should not confuse or mislead the reader by suggesting false implicatures or other pragmatic inferences. For example, a reader may be confused if he is told Sit by the brown wooden table in a context where there is only one table.

Pronouns

The simplest type of referring expressions are pronoun such as he and it. The linguistics and natural language processing communities have developed various models for predicting anaphor referents, such as centering theory,[11] and ideally referring-expression generation would be based on such models. However most NLG systems use much simpler algorithms, for example using a pronoun if the referent was mentioned in the previous sentence (or sentential clause), and no other entity of the same gender was mentioned in this sentence.

Definite Noun Phrases

There has been a considerable amount of research on generating definite noun phrases, such as the big red book. Much of this builds on the model proposed by Dale and Reiter.[12] This has been extended in various ways, for example Krahmer et al. [13] present a graph-theoretic model of definite NP generation with many nice properties. In recent years a shared-task event has compared different algorithms for definite NP generation, using the TUNA [5] corpus.

Spatial and Temporal Reference

Recently there has been more research on generating referring expressions for time and space. Such references tend to be imprecise (what is the exact meaning of tonight?), and also to be interpreted in different ways by different people.[14] Hence it may be necessary to explicitly reason about false positive vs false negative tradeoffs, and even calculate the utility of different possible referring expressions in a particular task context [15]

Other Kinds of Referring Expressions

Of course there are many other kinds of referring expressions, such as one-anaphora and event references, in addition to the ones described above. Unfortunately little research has been done on how to best generate such kinds of referring expressions.

References

  1. ^ T Winograd (1972). Understanding Natural Language. Academic Press, New York. Section 8.3.3, Naming Objects and Events
  2. ^ a b c D Appelt (1985). Planning English referring expressions. "Artificial Intelligence", 26:1–33.
  3. ^ a b D Appelt, A Kronfeld (1987). A computational model of referring. "In Proceedings of the 10th International Joint Conference on Artificial Intelligence (IJCAI)", pages 640–647, Milan.
  4. ^ A Kronfeld (1990). Reference and Computation: An Essay in Applied Philosophy of Language. "Cambridge University Press", Cambridge.
  5. ^ a b c d E Krahmer, K van Deemter (2012). Computational Generation of Referring Expressions: A Survey. Computational Linguistics 38:173-218 [1]
  6. ^ R Dale (1989). Cooking up referring expressions. In Proceedings of the 27th Annual Meeting of the Association for Computational Linguistics (ACL), pages 68–75.
  7. ^ R Dale (1992). Generating Referring Expressions: Constructing Descriptions in a Domain of Objects and Processes. TheMIT Press, Cambridge, MA.
  8. ^ E Reiter (1990). The computational complexity of avoiding conversational implicatures. In Proceedings of the 28th Annual Meeting of the Association for Computational Linguistics (ACL), pages 97–104, Pittsburgh, PA.
  9. ^ E Reiter, R Dale (1992). A fast algorithm for the generation of referring expressions. In Proceedings of the 14th International Conference on Computational Linguistics (COLING), pages 232–238, Nantes.
  10. ^ R Dale, E Reiter (1995). Computational interpretations of the Gricean maxims in the generation of referring expressions. Cognitive Science, 18:233–263.
  11. ^ M Poesio, R Stevenson, B di Eugenio, J Hitzeman (2004). Centering: A Parametric Theory and Its Instantiations. Computational Linguistics 30:309-363 [2]
  12. ^ R Dale and E Reiter (1995). Computational Interpretations of the Gricean Maxims in the Generation of Referring Expressions. Cognitive Science 19:233-263
  13. ^ E Krahmer, S van Erk, A Verleg. Graph-Based Generation of Referring Expressions. Computational Linguistics 23:53-72 [3]
  14. ^ E Reiter, S Sripada, J Hunter, J Yu, and I Davy (2005). Choosing Words in Computer-Generated Weather Forecasts. Artificial Intelligence 167:137-169.
  15. ^ R Turner, Y Sripada, E Reiter (2009) Generating Approximate Geographic Descriptions. Proceedings of ENLG-2009 [4]
Retrieved from "https://en.wikipedia.org/w/index.php?title=Referring_expression_generation&oldid=681158127"