Revisiting PRECIS: The Preserved Context Index System

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Revisiting PRECIS The Preserved Context Index
System

• Barbara H. Kwasnik
• School of Information Studies
• Syracuse University
• bkwasnik_at_syr.edu
• November 13, 2004
• ASIST SIG/CR Workshop

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Representation and Meaning

• An indexer analyzes a text and strives to
  ascertain meaning. Ideally this analysis
  anticipates a searcher at some future time,
  looking for text with the same meaning.
• But, meaning is not fixed at either end of this
  process.
• And even if the meaning is relatively unambiguous
  or stable, the terms used to represent it are
  not.

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The Dilemma

• Thus, most indexing processes encounter a dilemma
  at two levels
• Interpreting meaning as intended by the author
  and as construed by the potential user
• Choosing the terms to represent that meaning and
  that will enable this communication to be clear
  and as true as it can be. (Bearing in mind that
  such fidelity is a relative thing to begin with)

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Interacting Layers of Meaning

• Meaning is ascertained through several layers.
  These layers interact and and inform each other
• The lexical and morphemic level words and their
  forms
• The semantic level the meaning of the words
• The syntactic level the relationship of the
  words to each other, known as grammar
• The discourse level words interpreted in the
  context of text that is greater than the single
  sentence, and
• The pragmatic level words embedded in world
  knowledge, that is, the way they are used

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Meaning in Texts

• The meanings created through texts are often
  complex not readily reducible to a single
  concept. Representing them in too simple a way
  reduces the richness and fidelity of the
  representation.
• But representing complexity is very difficult,
  especially if we want to build in some stability
  through standardization.

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What to Do?

• Because words can be ambiguous, can have multiple
  senses and can change those senses over time,
  humans employ a range of strategies to work
  around this problem.
• One of the most useful and natural is the
  inclusion of context to disambiguate potential

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The Role of Context

• Indexers have employed many strategies to enhance
  the richness of representation. One of these
  techniques is to add contextual cues which may
• help disambiguate the terms possible multiple
  senses, and
• reveal how the term is being used, that is, its
  role in the text.

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Back-of-the-Book Indexes

• B.o.b.s are replete with context. In fact, a
  good index can be read and will give a fairly
  good indication of the content and scope of the
  text.
• Librarians
• education of
• job satisfaction of
• poor pay for
• The retention of natural order and prepositions
  helps make the meaning of individual terms clear
  (although not always).
• But these indexes are usually unique to the text
  to which they point and are quite difficult to
  maintain on a large scale.

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Traditional Thesauri

• A collection of subject terms structured as a
  hierarchy, with equivalence and associative
  relationships also noted.
• Community-college librarians
• UF Junior-college librarians
• BT Academic librarians
• RT University librarians
• These types of structures offer a semantic
  context.
• But, typically only one aspect of meaning is
  revealed at a time, and the representations only
  account for nouns.
• Associations among terms can only imply syntactic
  relationships. E.g., pasteurization and milk.

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Facet Analysis

• Strives to remedy limitations of
  one-dimensionality by enabling representation
  from a number of perspectives.
• Using Ranganathans classic dimensions we produce
  the string
• Time 12th Century
• Space Celtic
• Energy Embroidered
• Matter Felt
• Personality Slippers
• These strings can be presented in permuted order
  for access by any of the facets.

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PRECIS Preserved Context Indexing System

• Developed by Derek Austin in the early 1970s for
  subject indexing for the British National
  Bibliography
• Subsequently developed by him, with the
  assistance of Mary Dykstra, into an adaptable
  method of linking both the semantics and syntax
  of indexing terms.
• Goal was to represent meaning without disturbing
  the users immediate understanding.

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PRECIS Indexing Process (Incredibly Simplified)

• The indexer
• examines document, asking the following
  questions
• Did anything happen?
• If yes, to whom or what did it happen?
• Who or what did it?
• Where did it happen? (from Dykstra, 1987, p.9)
• mentally formulates a title-like phrase
• E.g., recruitment of teachers in American
  library schools
• analyzes terms syntactically

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PRECIS Indexing Process (Incredibly Simplified)

• determines role of each term
• (e.g., agent, location)
• selects appropriate role operator
• chooses lead terms.
• Term order is achieved by the operators and is
  based on context dependency. This means that each
  term in the string sets the next term into its
  obvious context.
• (e.g., Teachers. Library schools.)

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Producing the following entry

• United States
• Library schools. Teachers. Recruitment
• Library schools. United States
• Teachers. Recruitment
• Teachers. Library schools. United States
• Recruitment
• Recruitment. Teachers. Library schools. United
  States
• (from Austin, JDoc, 1974, p.49-51)

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Aspects of PRECIS Indexing

• Context is preserved The entire indexing
  statement appears at each lead term
• The permuted entries read naturally, which is
  achieved by the prescribed order of the role
  operators
• The terms are linked to a machine-held thesaurus
  (not described in this presentation) thereby
  providing possible sees and see alsos
• According to Austin, PRECIS can be adapted to
  other languages, e.g., those with inflection.
• The indexer determines meaning and codes the
  roles and lead terms, but the computer takes care
  of the permutations.

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Some Challenges

• Indexing with PRECIS requires a good knowledge of
  grammar
• In my opinion, the bottleneck comes at the first
  step articulating the title-like phrase.
• Its not clear how the terms provided by the
  indexer are harmonized with the thesaurus to
  produce consensual meaning.

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PRECIS as a Bridge

• PRECIS can take advantage of the semantic
  richness of a thesaurus, AND the contextual
  richness of the natural-like permuted phrases of
  back-of-the-book indexes.
• Could potentially add to the power of a facetted-
  string display by adding some explicit notion of
  operators among the facets.
• And, could take advantage of NLP techniques,
  which at this point are able to parse most
  syntactic roles, as well as phrases and names
  with about 80 accuracy without too much work.
  (personal communication, Liz Liddy)

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References

• Austin, Derek. PRECIS A Manual of Concept
  Analysis and Subject Indexing. 2nd ed. London
  British Library Bibliographic Services Division,
  1984.
• Austin, Derek. The development of PRECIS A
  theoretical and technical history. Journal of
  Documentation 30 (1) 1974 47-102.
• Dykstra, Mary. PRECIS A Primer. Rev. reprint.
  Metuchen, NJ London Scarecrow Press, 1987.