Dontopedia

Entity Object

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)

Entity Object has 6 facts recorded in Dontopedia across 2 references, with 1 live disagreement.

6 facts·5 predicates·2 sources·1 in dispute

Mostly:has attribute(2), rdf:type(1), has text(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound 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.

isPartOfIs Part of(2)

accessesAccesses(1)

Other facts (6)

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.

6 facts
PredicateValueRef
Has Attributetext[1]
Has Attributelabel[1]
Rdf:typeNer Entity[1]
Has TextEntity Text[2]
Has LabelEntity Label[2]
Is Indexed byEntity Index[2]

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.

typebeam/794f3163-d070-43d9-98eb-a13fac423ad2
ex:NEREntity
hasAttributebeam/794f3163-d070-43d9-98eb-a13fac423ad2
text
hasAttributebeam/794f3163-d070-43d9-98eb-a13fac423ad2
label
hasTextbeam/b27efc86-7008-4384-852a-049d06d255cb
ex:entity-text
hasLabelbeam/b27efc86-7008-4384-852a-049d06d255cb
ex:entity-label
isIndexedBybeam/b27efc86-7008-4384-852a-049d06d255cb
ex:entity-index

References (2)

2 references
  1. ctx:claims/beam/794f3163-d070-43d9-98eb-a13fac423ad2
    • full textbeam-chunk
      text/plain1 KBdoc:beam/794f3163-d070-43d9-98eb-a13fac423ad2
      Show excerpt
      text_es = "La empresa Apple comprara una startup britanica por mil millones de dolares." print(process_text(text_en, "english")) print(process_text(text_es, "spanish")) ``` ### 4. **Flair** - **Languages Supported**: Flair support
  2. ctx:claims/beam/b27efc86-7008-4384-852a-049d06d255cb
    • full textbeam-chunk
      text/plain1 KBdoc:beam/b27efc86-7008-4384-852a-049d06d255cb
      Show 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

See also

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