Several potential application of natural language processing have proven to be intractable. In this paper, we provide and overview of methods from library cataloguing and linguistics that have not yet been adopted by the natural language processing community and which could be used to help solve some of these problems

Guest, E

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Citation: 
 
Guest, E. (2009) Library Cataloguing and Role and Reference Grammar for 
Natural Language processing Applications. The 13th World Multi-Conference 
on Systemics, Cybernetics and Informatics: WMSCI 2009, July 10th - July 
13th, 2009. 
 
This paper was submitted and accepted; however, it was not presented / 
published due to non-attendance at the conference. 
 
 
Elizabeth Guest (2009) 
 
 
 
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 Library Cataloguing and Role and Reference Grammar for Natural Language processing 
Applications 
Elizabeth Guest 
Innovation North, Leeds Metropolitan University 
Leeds, LS6 3QS, UK 
 
ABSTRACT 
Several potential application of natural language processing 
have proven to be intractable. In this paper, we provide and 
overview of methods from library cataloguing and linguistics 
that have not yet been adopted by the natural language 
processing community and which could be used to help solve 
some of these problems.  
Keywords: library cataloguing, PRECIS, Role and Reference 
Grammar, Semantics, natural language processing  
1. INTRODUCTION 
 
Solutions for problems such as automatic marking of free text 
answers, automatic summarisation, and automatic semantic 
indexing of web pages, would be likely to have a major impact 
on our lives. However despite decades of work such 
applications have proven to be intractable. It may be that 
significant steps forward could be make by looking outside the 
standard techniques that are currently being explored and 
incorporating ideas from other disciplines. To this end, this 
paper provides an overview of methods and techniques from 
other disciplines that have not yet been adopted by the natural 
language community and which could be used to help solve 
some of these intractable problems. 
 
The three methods chosen are Role and Reference Grammar 
(RRG) [2], library cataloguing, and ULM [1], which is a 
semantic framework that attempts to both bridge the gap 
between syntax and semantics and handle ranges of meaning. 
Role and Reference Grammar is a linguistic theory similar to 
functional grammar. It is gaining a following in the linguistic 
community as various researchers apply it to a wide range of 
languages and plug the holes in the theory. This theory has 
attractions in that it has been shown to handle tricky 
grammatical structures in many different types of languages 
with little difficulty. It separates the most vital parts of the 
sentence from the modifiers (adverbs, adjectives, auxiliaries, 
and articles). This means that the core meaning can be extracted 
first and then the modifiers fitted in at a later stage. As long as 
the arguments and the verbs are in the correct order for English 
(subject verb object) then the sentence can be understood. It 
doesn’t matter if (for example) Chinese students forget the 
articles, the sentence can still be parsed and the meaning 
extracted. An important advantage of RRG is that it is based 
around the notion of a CORE, which contains a predicate 
(normally a verb) and its arguments. The CORE is structured in 
such a way that it is easy to obtain the meaning from the 
sentence. More details of RRG are given in the paper “Parsing 
using the Role and Reference Grammar Paradigm”, which has 
been submitted to this conference. Role and Reference 
Grammar includes a semantic paradigm based, like many 
others, on first order predicate logic. An investigation into 
semantic paradigms was performed and none were found that  
 
are really adequate to the task because they assume that words 
have distinct, well defined and non-overlapping meanings. In an 
attempt to solve this problem, a new semantic framework called 
ULM [1] was developed. This has not yet been thoroughly 
tested and will require refinement, but it is believed that it will 
be useful in tackling problems involving semantics. 
 
The need for methods to catalogue items held in libraries has 
been an issue ever since libraries existed – more than 4000 
years. Current methods enable someone searching for 
information in a library to find something about it relatively 
easily, particularly with on-line searching techniques. Librarians 
have already tackled many of the problems confronting those 
trying to get the semantic web up and running and it makes 
sense to see if they have anything to offer to make this task 
easier. 
 
2. LIBRARY CATALOGUING 
 
A library catalogue consists of entries containing metadata 
about each item in the library. The metadata includes all kinds 
of information about the item including the author(s), title, 
publisher, date of publication, edition, language, shelf mark, 
ISBN, price, physical description, type of material, key words, 
and much more. Metadata can be categorised into the following 
categories: 
• Structural 
• Indexing 
• Administrative 
• Descriptive 
 
Descriptive metadata is the metadata used to describe the 
contents of an item and is the metadata most important for 
searching a catalogue. A library index can be built from the 
descriptive metadata and a subject heading list or a thesaurus 
and the latter ensure that consistency in the descriptive metadata 
is maintained. Note that a thesaurus in this sense is not a 
dictionary of synonyms but an augmented taxonomy. Today 
with the advent of online searching, an index is no longer 
required because the system simply retrieves all entries 
containing the entered search terms. However, this does not 
mean that thesauri and subject heading lists are no longer 
required. On the contrary they are very important in that they 
specify a controlled vocabulary that is used for the metadata 
entries to ensure that different words are not used to describe 
the same concept. This ensures consistency in the metadata, and 
improves search results.  
 
Thesauri contain more complete information than a subject 
heading list as they contain both hierarchical and associative 
relationships as well as an alphabetical list of terms. Associative 
relationships contain all relationships that are not parent or child 
                                                 
relationships. They include sibling relationships. Some thesauri 
distinguish between generic parent-child relationships and part-
whole relationships. Therefore a thesaurus can provide both an 
alphabetical list of terms and a map of the subject area. It also 
documents preferred terms and synonyms of these preferred 
terms are included in the alphabetical list. The choice of 
preferred terms is systematic.These preferred terms are useful 
for search as they provide for consistent retrieval of relevant 
items in the catalogue: key words in the catalogue entries will 
contain only preferred terms. By using the thesaurus, non-
preferred search terms chosen by a user can be converted into 
the preferred terms. This means that no matter the terms found 
in the original item, retrieval by subject will be facilitated. The 
thesaurus is important for ensuring that items can be found even 
when someone searches using a different term. 
 
3. AUTOMATIC LIBRARY CATALOGUING 
 
There is a method of library cataloguing, PRECIS [3]. Which 
was discontinued during the 1980s becasue of the cost of 
manpower to do it. However, some librarians think it was better 
than the current methods, and would like to see it resurrected. It 
so happens that questions that someone using PRECIS has to 
answer are precisely those that Role and Reference Grammar is 
designed to answer. PRECIS  is a method for generating an 
index of materials. It was developed in the 1960s and part of the 
process was automated even then. Its best known use was to 
provide the alphabetical subject index to the British national 
bibliography. The index entries consist of a few words that 
provide a summary of what the document is or what it is about. 
The process involves the indexer examining the document and 
making a brief summary of what it is about. This summary 
statement is analysed by answering the following questions 
1) What happened? – the action 
2) To whom or what did it happen? – the object of the 
action 
3) Who or what did it? – the agent of the action 
4) Where did it happen? – location 
5) Are any of the concepts in the statement related in a 
whole-part relationship? 
 
This produces a list of terms and the cataloguer then decides 
which should be the terms that appear in the catalogue. In 
general all terms will be lead terms. Only terms that are very 
general relative to the subject of the thesaurus or those that 
would generate myriads of entries are excluded. 
 
An example (taken from the PRECIS book [3]) is 
Subject: planning the planting of vegetables 
String: (1) vegetables √ 
  (2) planting √ 
  (2) planning 
Entries: Vegetables 
   Planting. Planning 
  Planting. Vegetables 
   Planning 
Note that the ticks after the items denote lead terms. ‘planning’ 
is not a lead term because it is too general. The entries consist of 
several items which are in a specific order. The first line 
contains the lead term followed by ‘qualifiers’, which contains 
items higher up the list in reverse order. The second line 
contains the ‘display’, which contains items lower down the list 
in their input order. The numbers before each item in the list 
denotes its role. Roles are numbered as follows: 
      (0) the location of the action 
(1) the object of the action 
(2) the action 
(3) the agent of the action 
This denotes the filing order of the terms in the entry. They also 
play a role when the computer generates the entries from the 
string. 
 
When the indexer has made and organised the list of terms, it is 
checked against a list held in a file. If the list already exists then 
the appropriate metadata is added to the catalogue entry. If it is 
not in the file, the list of terms is passed to the person in charge 
of the thesaurus. This person checks the string against thesaurus 
entries to make sure that only preferred terms are used. In 
addition, the thesaurus is updated if any of the terms are not yet 
in the thesaurus. 
 
The thesaurus is an important part of the PRECIS process. It is 
used in the automatic generation of the index to generate ‘see’ 
entries which point the user to the preferred terms. It also 
generates ‘see also’ entries which point the user to narrower 
terms (child terms in the thesaurus hierarchy). 
The hardest part of the PRECIS process is generating 
and organising the list of terms. This part includes the analysis 
of compound terms, which today is part of constructing a 
thesaurus. However, the process of generating the list of terms 
is remarkably similar to the ideas behind Role and Reference 
Grammar (RRG). Role and Reference Grammar is primarily 
concerned with the roles of the items in a sentence and contains 
methods for extracting these. In the roles are given the 
following names 
(0) Periphery. Location is considered to be peripheral 
information.  
(1) The undergoer (the object of the action) 
(2) The predicate (the action) 
(3) The actor (the agent of the action) 
Everything within the design of RRG is to make the 
identification of the predicate, the undergoer and the actor 
within a sentence easy. Note that (1) can also be the subject of 
an instransitive verb, but this is no problem for RRG: it is just 
the ‘priviledged syntactic argument’. The PSA or priviledged 
syntactic argument is a device within RRG to identify the 
subject of an intransitive verb and to handle passive 
constructions appropriately. The only thing that might cause 
difficulty to RRG is the location, but this is really just a case of 
looking for locations in the PERIPHERY, which is not hard if 
the words are labelled correctly in the dictionary used for 
tagging. However, even this may not be necessary: a simple call 
to WordNet to see if the word comes under location may be all 
that is required. An examination of the preposition used to 
introduce the location will also provide clues. 
When PRECIS was in use1, much of the role of 
indexer was to apply world knowledge to the terms, especially 
when it came to dealing with compound terms. But if this is 
moved to the thesaurus, virtually all of the analysis of the 
statement of what the document is about can be automated 
An advantage of building a PRECIS index is that an 
appropriate section of the index could be presented for the user 
to browse. This is almost certainly quicker that trying to 
interpret titles. In addition, information about the faculty in 
which the learning object was developed can be added, which 
will give the user additional information about whether or not 
the item may be useful. 
 
4. Universal Lexical Metalanguge (ULM) 
 
 
1 For instance in providing the subject index to the British 
national bibliography 1971-1986 
 
The Universal Lexical Metalanguage, ULM, is the 
outcome of a collaboration between a computer scientist and a 
linguist to find a better way of doing semantics. The result is a 
framework that is a combination of a lexicon and a knowledge 
representation system that has the following properties: 
• strong link between syntax and semantics 
• use of a universal semantic metalanguage 
• Rich and expressive semantic structure (formal 
language) and explicit encoding of the argument 
of verbs to provide contextual information. 
• use of fuzzy logic and fuzzy set theory to mimic 
how people use language 
• explicit separation of objects, predicates, and 
operators 
 
ULM provides a semantic knowledge representation based on 
meaning, and its theoretical stance allows us to develop 
powerful reasoning algorithms that enable it to be applied to 
many applications which require some analysis of meaning. For 
example algorithms for comparing sentences for similar 
meaning and reasoning with context can be applied to the 
problem of automatic marking of short free text answers. ULM 
has been presented to several people and some interest has been 
raised for its application to automatic translation (the UK 
security services), automatic marking, plagiarism detection 
(JISC), and for information retrieval within specific domains 
(several companies in Spain). These potential users see its 
potential to provide a more precise and elegant solution than 
existing algorithms which mainly base their search engine from 
a source word to a target word. 
ULM is a schema consisting of several interlinking parts. This 
schema is based around two separate ontologies: one for 
predicates (generally verbs) and one for objects, which are 
arguments of predicates (generally nouns). Each predicate and 
each object is defined using a universal semantic metalanguage. 
This metalanguage consists of universal primitives and 
functions that will enable a full description of any language, and 
a mapping between languages.  
 
The ontologies are linked to each other so that, for example it is 
possible to work out which prepositional phrases are arguments 
or argument adjuncts of the predicates, and which give other 
information such as time and place. Predicates and objects are 
linked together so that predicates are directly attached to their 
possible arguments and objects are attached to predicates that 
are applicable. These latter links can help to pin down the 
meaning of the predicate when applied to this particular object. 
This also builds in a framework for knowledge representation as 
it would be fairly easy to deduce from such a network what 
objects are used for. In addition we propose to link objects 
together into some kind of fuzzy conceptual ontology so that, 
for example, the word “meal” can be attached to “table”, 
“cutlery”, “food”, “drink”, “human” etc, so that a whole context 
can be derived (as each object is also attached to appropriate 
predicates).A schematic diagram of this schema showing how 
parts interact is given in Figure 3. 
 
In relation to the definitional apparatus, each prime will be at 
the top of its own hierarchy defined by a set of hyponyms 
derived from these semantic primes using universal functions 
applied to the intervals and a formal definitional language. 
These hierarchies each define a separate domain and provide a 
disconnected but well defined set of domains, based on 
universal primitives. Each derived word will inherit some or all 
of the intervals from the relevant prime and these intervals will 
describe the range of meaning of this word. These derived 
words are language specific because the primes are language 
specific. However, the metalanguage with which they are 
described is universal. 
 
Words that contain ideas from more that one domain will sit 
between these domains Each word derived in this way will also 
be language specific. However, it will be possible to map 
concepts between languages by looking up common sets of 
intervals used and common definitions of words.  
 
A schematic diagram of the predicate ontology is given in figure 
1 and a more detailed view of how this would work in practise 
is given for English verbs in Figure 2 
 
 
Figure 1: A schematic diagram of the predicate semantic 
domain. 
 
 
 
 
 
 
Figure 3: Overview of the new semantic framework 
 
5. Conclusion 
 
The methods briefly described above could be applied to several 
application including automatic library cataloguing, the 
semantic web, and automatic marking of free text answers. Of 
these the application of automatic library cataloguing has been 
described in most detail, but this clearly has implications for the 
semantic web. If automatic library cataloguing is possible, we 
are not far from being able to catalogue web pages in a 
meaningful way. Methods for automatic marking of short, free 
text answers would use the methods of automatic library 
cataloguing augmented with ULM to handle semantic 
information. Automatic cataloguing would also benefit from the 
use of ULM, but given a suitable thesaurus (such as the Library 
of Congress Subject Heading list), it should be possible to 
manage with existing semantic repositories such as WordNet.  
 
  
6. References 
 
[1]. Guest, E. and R. Mairal Usón, "Lexical Representation 
Based on a Universal Metalanguage". RAEL, Revista 
Española de Lingüística Aplicada, 4 2005 pp. 125-173. 
[2]. Van Valin, R.D.J., Exploring the Syntax-Semantics 
Interface.  Cambridge University Press.2005 
[3]. Austin, D., PRECIS: A Manual of Concept Analysis and 
Subject Indexing.  The British Library 1984  
 
Figure 2: A partial ontology of English verbs. The arrows 
show that words that are derived from more than one prime 
inherit the intervals from all relevant primes. 
 
 
 
 
 
 
 
 


Library Cataloguing and Role and Reference Grammar for Natural Language processing Applications

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