Synset
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
Synset has 11 facts recorded in Dontopedia across 7 references, with 1 live disagreement.
Mostly:rdf:type(6), ex:has method(1), ex:contains lemmas(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (3)
Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
belongsToManyBelongs to Many(1)
- Lemma
ex:lemma
isMemberOfIs Member of(1)
- Lemma
ex:lemma
returnsEntityReturns Entity(1)
- Wn Synsets
ex:wn-synsets
Other facts (11)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Synset | [1] |
| Rdf:type | Linguistic Concept | [2] |
| Rdf:type | Variable | [3] |
| Rdf:type | Synset Object | [4] |
| Rdf:type | Linguistic Concept | [6] |
| Rdf:type | Word Net Concept | [7] |
| Ex:has Method | Lemmas | [1] |
| Ex:contains Lemmas | Lemma Collection | [1] |
| Has Method | Lemmas | [4] |
| Contains | Lemmas | [5] |
| Is Returned by | Wn Synsets | [5] |
Timeline
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
References (7)
ctx:claims/beam/82dc87bd-74b8-4fb6-be5d-469ed934c86c- full textbeam-chunktext/plain1 KB
doc:beam/82dc87bd-74b8-4fb6-be5d-469ed934c86cShow excerpt
nlp = spacy.load("en_core_web_sm") lemmatizer = WordNetLemmatizer() def get_wordnet_pos(treebank_tag): """Converts treebank POS tags to WordNet POS tags.""" if treebank_tag.startswith('J'): return wordnet.ADJ elif treeb…
ctx:claims/beam/6f825f15-5c97-4244-84f2-e40ee078d6ae- full textbeam-chunktext/plain1 KB
doc:beam/6f825f15-5c97-4244-84f2-e40ee078d6aeShow excerpt
- **Contextual Relevance**: Consider using a context-aware approach to filter synonyms based on the context of the query. - **Dependency Parsing**: Use dependency parsing to better understand the relationships between words in the query. #…
ctx:claims/beam/4be5ccbb-c1b7-4c71-b494-78fd7c33ee6fctx:claims/beam/b27efc86-7008-4384-852a-049d06d255cb- full textbeam-chunktext/plain1 KB
doc:beam/b27efc86-7008-4384-852a-049d06d255cbShow excerpt
entities = [(ent.text, ent.label_) for ent in doc.ents] # Extract synonyms for each token synonyms = [] for token in tokens: pos = get_wordnet_pos(nltk.pos_tag([token])[0][1]) synsets = wordnet.synsets(t…
ctx:claims/beam/5911aad5-31b8-481d-9758-9632ba044f91- full textbeam-chunktext/plain1 KB
doc:beam/5911aad5-31b8-481d-9758-9632ba044f91Show excerpt
2. **Download WordNet**: Download the WordNet data using NLTK. ```python import nltk nltk.download('wordnet') ``` 3. **Expand Synonyms Using WordNet**: ```python from nltk.corpus import wordnet as wn def expand_synony…
ctx:claims/beam/869acbd5-0cda-40b0-94b3-06d5699021f2- full textbeam-chunktext/plain1 KB
doc:beam/869acbd5-0cda-40b0-94b3-06d5699021f2Show excerpt
elif term.endswith("ed"): return [term[:-2] + "ing"] # WordNet approach synonyms = set() for syn in wn.synsets(term): for lemma in syn.lemmas(): synonyms.add(lemma.name()) # NLP appr…
ctx:claims/beam/57e2ea52-f5cb-4239-bf9f-3147a3b2efbc- full textbeam-chunktext/plain1 KB
doc:beam/57e2ea52-f5cb-4239-bf9f-3147a3b2efbcShow excerpt
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') model = BertModel.from_pretrained('bert-base-uncased') def get_context_aware_synonyms(word, context_sentence): inputs = tokenizer(context_sentence, return_tensors='pt', pad…
See also
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