Wendy G Lehnert
Biographic Data
| ID | 1617477 |
|---|---|
| NAME | Wendy G Lehnert |
| GIVEN NAMES | Wendy G |
| FAMILY NAME | Lehnert |
| SIGNATURE | LEHNERT W G |
| AFFILIATIONS | University of Massachusetts Amherst |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 7 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1978 |
| LATEST PUBLICATION YEAR | 1997 |
| H-INDEX | 1 |
Information extraction
Practical natural language processing applications typically confront significant difficulties with lexical ambiguity, knowledge‐engineering bottlenecks, and brittle processing techniques that fail to handle unrestricted input in a robust fashion. However, recent research efforts suggest that these problems can be successfully negotiated for an important class of applications. Information extraction systems operate in restricted discourse domains…
A survey of question answering in natural language processing
Thematic knowledge structures in the understanding and generation of narratives∗
Plot units are thematic representations of patterns of goal relationships and events used in comprehension. Subjects’ sensitivity to these thematic patterns in stories were examined in three experiments. In the first experiment, subjects were asked to sort stories into groups that had “the same kind of plot.” The results showed that subjects sorted according to thematic patterns (instead of specific story content): For example, they would disting…
The process of question answering
Thematic knowledge structures in the understanding and generation of narratives∗
Plot units are thematic representations of patterns of goal relationships and events used in comprehension. Subjects’ sensitivity to these thematic patterns in stories were examined in three experiments. In the first experiment, subjects were asked to sort stories into groups that had “the same kind of plot.” The results showed that subjects sorted according to thematic patterns (instead of specific story content): For example, they would disting…
Information extraction
Practical natural language processing applications typically confront significant difficulties with lexical ambiguity, knowledge‐engineering bottlenecks, and brittle processing techniques that fail to handle unrestricted input in a robust fashion. However, recent research efforts suggest that these problems can be successfully negotiated for an important class of applications. Information extraction systems operate in restricted discourse domains…
The process of question answering
Thematic knowledge structures in the understanding and generation of narratives∗
Plot units are thematic representations of patterns of goal relationships and events used in comprehension. Subjects’ sensitivity to these thematic patterns in stories were examined in three experiments. In the first experiment, subjects were asked to sort stories into groups that had “the same kind of plot.” The results showed that subjects sorted according to thematic patterns (instead of specific story content): For example, they would disting…
A survey of question answering in natural language processing
Information extraction
Practical natural language processing applications typically confront significant difficulties with lexical ambiguity, knowledge‐engineering bottlenecks, and brittle processing techniques that fail to handle unrestricted input in a robust fashion. However, recent research efforts suggest that these problems can be successfully negotiated for an important class of applications. Information extraction systems operate in restricted discourse domains…
Artificial Intelligence (3 works) · Computer Science (3 works) · Information retrieval (2 works) · Natural language processing (2 works) · Natural Language Processing Techniques (2 works) · Topic Modeling (2 works) · Ambiguity (1 work) · Child and Animal Learning Development (1 work) · Class (philosophy (1 work) · Cognitive psychology (1 work)