1. Computers are increasingly being used for natural language processing.

2. Computational questions have become central, not just in natural language processing applications, but also in theoretical discussions within linguistics.

3. Coreference resolution plays an important role in natural language processing.

4. Anaphora resolution is a key step in Natural Language Processing (NLP) and a kernel task in many language engineering applications.

5. Automatic summarization is an important issue in natural language processing.

6. Maximum entropy model provides a natural language processing method, and proposes a structured program of medical text information combined with standard terminology for health care.

7. For automatic natural language processing, the words must be stemmed.

8. NLP ( Natural Language Processing ) is an important branch of Artificial Intelligence.

9. QA is a high level application of natural language processing.

10. Japanese syntactic analysis is the kernel content in natural language processing and machine translation.

11. During the past half century the development of Natural Language Processing has involved such courses as mechanical translation, Natural Language Understanding, and Information Retrieval.

12. The goal is to build the natural language processing and text mining platform in Tencent.

13. Speech recognition and natural language processing are technologies still in their infancy.

14. In the field of Natural Language Processing, one important way of acquiring semantic information is Semantic Role labelling (SRL).

15. The automatic transcription, annotation and retrieval of broadcasting news requires automatic speech recognition, natural language processing and information retrieval technologies.

16. Open domain question answering (QA) represents a challenge of natural language processing, aiming at returning exact answers in response to natural language questions.

17. At the time of the rapid development of technology, the ambiguity problem has become one of the bottlenecks of natural language processing.

18. Word Segmentation is a fundamental problem of the Chinese Natural Language Processing.

19. The parsing technique is one of the key techniques in natural language processing.

20. Literary language processing deserves its due attention in the current research atmosphere of Natural Language Processing ( NLP ) .

21. Automatic alignment of parallel corpora is an important research subject in natural language processing area.

22. Identification of translingual equivalence of named entities is substantial to multilingual natural language processing.

23. The computer readable electronic dictionary is the foundation for all natural language processing, especially for the system of machine translation.

24. Word Sense Disambiguation ( WSD ) is a difficult issue in many fields of natural language processing, e.

25. Word sense tagging is one of the most difficult problem in natural language processing.

26. Finding base noun phrase is very important in the field of natural language processing.

27. They reflect the development and evolution trend of lexics, become concerns of Linguistics and make big challenge to Natural Language Processing.

28. Natural language interface is one of the most hopeful fields in the research on Natural Language Processing.

29. The Chinese semantic knowledge base system is a very important part of language knowledge engineering of Chinese semantic resource in natural language processing.

30. The representation and application of semantic knowledge is an important factor for Natural Language Processing (NLP).

31. Word sense tagging has always been important in natural language processing.

32. Morphological analysis is the foundation task for most natural language processing.

33. The representation and application of semantic knowledge is an important factor for Natural Language Processing.

34. We report experiments on song lyrics based on natural language processing techniques.

35. Word sense disambiguation is one of the difficult problems in natural language processing.

36. Through a series of large-scale evaluations, TDT has become a hot problem for worldwide research in the fields of natural language processing, especially in information retrieval.

37. Natural language interface is one of the most hopeful applied fields in the research on Natural Language Processing.

38. In addition, proper names recognition give prop to the natural language processing in the field of information extraction, question answering system and so on.

39. The quantitative research of semantic relation between words is an essential subtask for some natural language processing task.

40. Due to the uncertainty of the natural language meaning and difficulties of the semantic formalization, semantic processing becomes the key problem of Natural Language Processing.

41. These types of systems include advanced natural language processing systems that can discover new terms and relationships by analyzing content (such as document text in ECM systems).

42. Areas of emphasis include: artificial intelligence, natural language processing, and pattern and voice recognition.

43. This class introduces students to the basics of Artificial Intelligence, which includes machine learning, probabilistic reasoning, robotics, and natural language processing...

44. Identification of translingual equivalence of named entities is substantial to natural language processing.

45. Annotation is the keystone of the knowledge representation of any natural language processing ( NLP ) research.

46. CIP aims to be a natural language processing suit of Chinese.

47. Spelling correction is one of the hot spots in recent natural language processing research.