Mirrors-Web
A Demonstrator for Automatic Thesaurus Derivation
User's
Guide
|
|
|
|
Complete Thesaurus Listings
|
|
The user may specify one or more bases to have their derived thesaurus entries listed in one document, with the entries in alphabetical order. For each base a category may be specified, to identify the source of the entries in the merged list. Thus, specifying "a" after AJfull and "v" after Vfull will lead to the addition of "(a)" and "(v)" after the respective entries. The number of entries to be listed may also be specified. It is recommended that large bases are listed a few hundred entries at a time. Furthermore the same parameters as in the case of single entries may be specified: Extended bases, Language, Synsetlimit and Overlapthreshold. Finally the user may choose to exclude entries and senses where no hyperonyms, hyponyms, synonyms or related words have been found, and also "starred" entries, which is relevant for bases with only partial information from the corpus. The starred entries are entries for which the bases only contain limited information. |
Word Bases
The word bases currently available are listed below, where AJfull, Nfull, Vfull, Aone, None
and Vone are based on automatic word alignment of the corpus
by means of Sindre Sørensen's word alignment program, base-0102, gkverbs2 and rett on manually extracted translational
correspondences in the corpus, and god2dict, handle2dict and rett2dict on automatically extracted
correspondences from a bilingual dictionary. (For space reasons, not all the
bases are accessible at all times; see under the individual base below.) The
first six bases hence reflect the shortcomings of the morphological tagging
of the corpus and the preliminary status of the automatic word alignment,
which has an estimated precision of .84 and an estimated recall of .62.
Hence, there is much "noise" in those bases, but there are also
encouraging properties.
AJfull
N: 4369
entries
E: 4093
entries
Automatically extracted
adjectives. The corpus has been automatically word-aligned (see above), and
then all adjectives with their sets of translations in the corpus, limited to
adjectives, have been extracted.
AJone
N:
2532entries
E: 2436
entries
Automatically extracted
adjectives from the same material as AJfull, except that
translational correspondences that occur only once in the corpus have been
disregarded. This removes much noise, but also quite a few desirable results.
Nfull
N: 16299
entries
E: 10385
entries
Automatically extracted
nouns. The corpus has been automatically word-aligned (see above), and then
all nouns with their sets of translations in the corpus, limited to nouns,
have been extracted.
None
N:
12408 entries
E: 9494
entries
Automatically extracted
nouns from the same material as Nfull, except that
translational correspondences that occur only once in the corpus have been
disregarded. This removes much noise, but also quite a few desirable results.
Vfull
N: 2928
entries
E: 2888
entries
Automatically extracted
verbs. The corpus has been automatically word-aligned (see above), and then
all verbs with their sets of translations in the corpus, limited to verbs,
have been extracted.
Vone
N:
2427 entries
E: 2376
entries
Automatically extracted verbs
from the same material as Vfull, except that translational
correspondences that occur only once in the corpus have been disregarded.
This removes much noise, but also quite a few desirable results.
base-0102:
N: 2796
entries
E: 724
entries
Manually extracted
translation correspondences starting from the Norw. adjective 'god' and the
nouns 'tak' and 'selskap' and going back and forth 4 times (extracted by
Helge Dyvik and Martha Thunes).
gkverbs2:
N: 2698
entries
E: 1036
entries
Manually extracted
translation correspondences comprising verbs, starting from the Norw. verbs
'handle' and 'ta' (extracted by Gunn Inger Lyse and Kjersti Drøsdal
Vikøren).
rett:
N: 208
entries
E: 1280
entries
Manually extracted
translation correspondences (for a masters thesis by Gunn Inger Lyse)
starting from the Norw. noun and adjective 'rett' (entered as
"rettN" and "rettA" respectively).
god2dict:
N: 7185
entries
E: 2725
entries
This base is not taken
from the ENPC corpus: It is based on automatically extracted translation
correspondences from Kunnskapsforlaget's big
English-Norwegian/Norwegian-English dictionary (c. 217.000 entries) (in
connection with a masters thesis by Karen Halling), starting with the
adjective 'god' and going back and forth 5 times. Sense divisions in the
dictionary have been disregarded: for each dictionary entry the union of its
translations across senses has been extracted. Thus, the sense divisions in the
thesaurus entries are derived by the Mirrors method.
handle2dict:
N:
4701 entries
E:
593 entries
This base, in the same
way as god2dict, is based on automatically extracted translation correspondences
from Kunnskapsforlaget's English-Norwegian/Norwegian-English dictionary,
starting with the verb 'handle' and going back and forth 5 times.
rett2dict:
N: 7670
entries
E: 1252
entries
This base, in the same
way as god2dict, is based on automatically extracted translation
correspondences from Kunnskapsforlaget's English-Norwegian/Norwegian-English
dictionary, starting with the noun 'rett' and going back and forth 5 times.
Do you want
to analyse your own translational word base? Contact Helge
Dyvik
Extended bases
The user may choose to operate on automatically
'extended' versions of the bases. This concept is explained here (in Norwegian). Extended bases generally (but
not always) give the best results.
Synset Limit
Synset Limit can be set. This concept is explained on p. 16 of
MirrorsPaper. It influences the division of related words
into 'synonyms', 'related words', 'hyperonyms' and 'hyponyms'. In general,
the higher the Synset Limit, the larger the number of synonyms and related
words, and the smaller the number of hyperonyms and hyponyms (i.e., a
"flatter" hierarchy). If no value is given, Synset Limit is
calculated automatically on the basis of the size of the semantic fields (1/4
of the number of senses in the field, but maximum 20 and minimum 5). The
value should be a whole number, 20 being a useful default. The range 3 - 25
is recommended.
Overlap Threshold
Overlap Threshold can be set. This concept is explained on p. 17
of MirrorsPaper. It influences the granularity of the division
of each sense into mutually related subsenses. The value should be a number
between 0 and 1, with 0.05 as a recommended default. In general, the higher
the Overlap Threshold, the more subsenses.
Lattices
Below the headline of each Sense in the entry, the option Lattice can be chosen. This concept is
explained on p. 12 ff. of MirrorsPaper. Sets of features have automatically been
assigned to the words in the bases based on the network of translational
relations, and the feature sets form lattice structures based on inclusion
and overlap among the sets. According to the hypothesis this lattice
structure expresses semantic relations like hypero- and hyponymy, and
semantic closeness is assumed to be reflected in closeness in the lattice.
The thesaurus entries have been derived from the information in the lattices.
By
clicking on Lattice
part of the lattice structure surrounding the word sense is displayed: All
nodes dominated by the word sense itself, and all its mother and grandmother
nodes, with the sublattices dominated by them. In web browsers with the
appropriate software it is possible to browse further parts of the lattice by
clicking on nodes to see the sublattices similarly associated with them.
Questions and comments
to Helge
Dyvik