As large corpora are published, researchers are increasingly likely to base their investigations on balanced, focused subsets that were derived from corpora produced for entirely different reasons. For instance, the Switchboard database, originally collected for speaker identification research, has since been used as the basis for published studies in speech recognition, word pronunciation, disfluency, syntax, intonation, and discourse structure. The motivations for recycling linguistic corpora include the desire to save time and effort, the desire to work on material available to others for replication, and sometimes a desire to study more naturalistic forms of linguistic behavior than would be possible otherwise. The process of choosing a subset for such a study may count as a non-trivial contribution in itself.
In addition to selecting an appropriate subset of a corpus, this new work could involve reformatting a text file (e.g., converting to XML), renaming files, retokenizing the text, selecting a subset of the data to enrich, and so forth. Multiple research groups might do this work independently, as illustrated in Figure 11-5. At a later date, should someone want to combine sources of information from different versions, the task will probably be extremely onerous.
to ken ¡zed and tagged
Research Group 1:
discard tags, retokenize, annotate named-entities
Research Group 2:
sentence segmentation, -discard punctuation, parse
Research Group 3:
select subset of sentences and annotate co reference .
Research Group 4:
select subset of sentences and label semantic roles
Figure 11-5. Evolution of a corpus over time: After a corpus is published, research groups will use it independently, selecting and enriching different pieces; later research that seeks to integrate separate annotations confronts the difficult challenge of aligning the annotations.
The task of using derived corpora is made even more difficult by the lack of any record about how the derived version was created, and which version is the most up-to-date.
An alternative to this chaotic situation is for a corpus to be centrally curated, and for committees of experts to revise and extend it at periodic intervals, considering submissions from third parties and publishing new releases from time to time. Print dictionaries and national corpora may be centrally curated in this way. However, for most corpora this model is simply impractical.
A middle course is for the original corpus publication to have a scheme for identifying any sub-part. Each sentence, tree, or lexical entry could have a globally unique identifier, and each token, node, or field (respectively) could have a relative offset. Annotations, including segmentations, could reference the source using this identifier scheme (a method which is known as standoff annotation). This way, new annotations could be distributed independently of the source, and multiple independent annotations of the same source could be compared and updated without touching the source.
If the corpus publication is provided in multiple versions, the version number or date could be part of the identification scheme. A table of correspondences between identifiers across editions of the corpus would permit any standoff annotations to be updated easily.
Sometimes an updated corpus contains revisions of base material that has been externally annotated. Tokens might be split or merged, and constituents may have been rearranged. There may not be a one-to-one correspondence between old and new identifiers. It is better to cause standoff annotations to break on such components of the new version than to silently allow their identifiers to refer to incorrect locations.
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