Datasets:

jeffreyschultz
/

wordnet

This guide explains the structure of the WordNet files used in this dataset project, how this adapter parses them, and how to interpret the resulting records for research workflows.

Scope

This project packages WordNet 3.0 lexical database files for four parts of speech:

noun
verb
adjective
adverb

The adapter supports three variants:

data - synset records (data.noun, data.verb, data.adj, data.adv)
index - lemma index records (index.noun, index.verb, index.adj, index.adv)
exceptions - morphology exceptions (noun.exc, verb.exc, adj.exc, adv.exc)

Source Files In This Project

Under datasets/wordnet/data:

data.noun, data.verb, data.adj, data.adv
index.noun, index.verb, index.adj, index.adv
noun.exc, verb.exc, adj.exc, adv.exc

Important: WordNet files begin with license/header text before structured records. Those rows are valid file content but not structured lexical records.

Canonical Format References

Primary references for WordNet 3.0 file formats:

Princeton wndb(5WN): data/index/exception file grammar
Princeton wninput(5WN): pointer symbols and lexical conventions

See:

Core Concepts

Synset: a set of synonymous word senses.
synset_offset: byte offset used as an address into data.* files.
ss_type: part-of-speech/synset type marker (n, v, a, s, r).
Pointer: typed relation from one synset (or specific word sense) to another.
source/target: a four-hex-digit field that distinguishes semantic and lexical pointers.

Synset Identity

synset_offset alone is not globally unique across all POS files. Use (synset_offset, pos) as the unique synset key.

Raw File Grammar

`data.*` Files

Per wndb(5WN), data lines are:

synset_offset lex_filenum ss_type w_cnt word lex_id [word lex_id ...] p_cnt [ptr ...] [frames ...] | gloss

Where:

synset_offset: 8-digit decimal byte offset.
lex_filenum: 2-digit decimal lexical file id.
ss_type: one of n, v, a, s, r.
w_cnt: 2-digit hexadecimal count of words in the synset.
word: token, underscores for spaces (adjectives may include markers like (p)).
lex_id: 1-digit hexadecimal sense discriminator within lexicographer files.
p_cnt: 3-digit decimal pointer count.
ptr:

pointer_symbol target_synset_offset pos source/target

source/target: four hexadecimal digits, split as ss tt:
- 0000 means semantic pointer (synset-to-synset)
- non-zero means lexical pointer from source word number ss to target word number tt
frames (verbs only):

f_cnt + f_num w_num [ + f_num w_num ... ]

gloss: free text after |.

`index.*` Files

Per wndb(5WN), index lines are:

lemma pos synset_cnt p_cnt [ptr_symbol ...] sense_cnt tagsense_cnt synset_offset [synset_offset ...]

Where:

lemma: lower-case lemma/collocation (_ for spaces).
pos: n, v, a, r.
synset_cnt: number of senses/synsets for this lemma in POS.
p_cnt: number of pointer symbols listed.
ptr_symbol: pointer symbol types seen for lemma senses.
sense_cnt: redundant historical count field.
tagsense_cnt: number of tagged (frequency-ranked) senses.
trailing synset_offset list length should equal synset_cnt.

`*.exc` Exception Files

Per wndb(5WN), exception lines are:

inflected_form base_form [base_form ...]

These map irregular inflections to one or more base forms.

Pointer Symbols You Will See

This project normalizes common pointer symbols to labels when parsing data.*.

Symbol	Label
`!`	antonym
`@`	hypernym
`@i`	instance_hypernym
`~`	hyponym
`~i`	instance_hyponym
`#m`	member_holonym
`#s`	substance_holonym
`#p`	part_holonym
`%m`	member_meronym
`%s`	substance_meronym
`%p`	part_meronym
`=`	attribute
`+`	derivationally_related_form
`;c`	domain_of_synset_topic
`-c`	member_of_domain_topic
`;r`	domain_of_synset_region
`-r`	member_of_domain_region
`;u`	domain_of_synset_usage
`-u`	member_of_domain_usage
`*`	entailment
`>`	cause
`^`	also_see
`$`	verb_group
`&`	similar_to
`<`	participle_of_verb
`\\`	pertainym_or_derived_from_adjective

Meaning and allowed POS combinations are defined by WordNet documentation.

Adapter Parsing Behavior

Variant `data` with `parse_records=true`

Adds structured fields:

is_record
offset, synset_offset
lex_filenum
ss_type
w_cnt, word_count
words (list of objects)
lemmas (normalized with spaces)
p_cnt, pointer_count
pointers (list of objects)
frames (list of verb frame objects; usually empty for non-verbs)
gloss
parse_error (flag when line partially matches but is malformed)

words entries include:

word
lemma
marker (for adjective markers like a, p, ip)
lex_id
lex_id_int
word_number

pointers entries include:

symbol
label
target_offset
pos
source_target
source_word_number
target_word_number
is_semantic

frames entries include:

frame_number
word_number
applies_to_all_words

Variant `index` with `parse_records=true`

Adds:

is_record
lemma, lemma_text
pos
synset_cnt
p_cnt
ptr_symbols
sense_cnt
tagsense_cnt
synset_offsets
parse_error

Variant `exceptions` with `parse_records=true`

Adds:

is_record
inflected_form, inflected_form_text
base_forms, base_forms_text

Header/License Row Handling

Non-record lines are expected at the top of files.

Parsed output marks these as is_record=false.
WordNet dataset config enables automatic filtering of these rows when parsing.

Project default in datasets/wordnet/dataset.json:

{
  "adapter_defaults": {
    "records_only": true
  }
}

Practical effect:

If you run with --parse-records, non-record rows are removed by default.
To keep raw non-record rows, set records_only=false.

Research Workflows

Quick CLI Usage

Parse data records and keep only true records (default behavior):

python -m tether.datasets run-dataset wordnet \
  --base-dir datasets/wordnet \
  --variant data \
  --parse-records \
  --json

Disable filtering for diagnostics/audit:

python -m tether.datasets run-dataset wordnet \
  --base-dir datasets/wordnet \
  --variant data \
  --parse-records \
  --option records_only=false \
  --json

Build parquet artifact bundle for analysis:

python -m tether.datasets prepare-dataset wordnet \
  --base-dir datasets/wordnet \
  --variant data \
  --parse-records \
  --output-dir artifacts/wordnet-research \
  --format parquet \
  --json

Example Analysis Ideas

Build graph edges from pointers using (synset_offset, ss_type) keys.
Compare lexical vs semantic relation rates via is_semantic.
Analyze gloss lengths, lemma counts (word_count), and pointer density (pointer_count).
Filter by specific pointer symbols (for example @ hypernym, ~ hyponym).

Recommended Quality Checks

Assert no remaining is_record=false rows in final analysis datasets when using defaults.
Track parse_error=true counts as ingestion quality telemetry.
Validate that index len(synset_offsets) == synset_cnt for parsed records.

Known Caveats

Some WordNet tokens contain punctuation and abbreviations (A.D., B.C.).
Not all pointer symbols apply to all parts of speech.
Exception files may include forms not present in your selected downstream subset.
Sense ranking in index files depends on WordNet tag counts and ordering conventions.

Citation And License

Citation: Miller (1995), WordNet: A Lexical Database for English.
License: WordNet 3.0 license (Princeton University), included in source files.

Use source-level attribution and license text in downstream publications and releases as required.

WordNet 3.0 Research Guide