Triple

T683713
Position Surface form Disambiguated ID Type / Status
Subject Elena Delle Donne E13236 entity
Predicate givenName P17 FINISHED
Object Elena E86412 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Elena | Statement: [Elena Delle Donne, givenName, Elena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elena
Context triple: [Elena Delle Donne, givenName, Elena]
  • A. Elena chosen
    Elena is a feminine given name of Greek origin, commonly used in many languages as a variant of Helen or Helena.
  • B. Valeria
    Valeria was a Roman imperial princess and later empress, best known as the daughter of Emperor Diocletian and for her tragic fate during the political turmoil of the Tetrarchy.
  • C. Yelena Belova
    Yelena Belova is a Marvel Comics-trained assassin and the second Black Widow, known in the Marvel Cinematic Universe as a sharp-witted spy and fighter closely tied to Natasha Romanoff.
  • D. Rebeca
    Rebeca is a feminine given name, commonly used in Spanish- and Portuguese-speaking countries, that is a variant of the name Rebecca.
  • E. Alexa Vega
    Alexa Vega is an American actress and singer best known for playing Carmen Cortez in the Spy Kids film series.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a4933e0f98819097d22766c49b61b8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a070d4c08190a510a8f9c1ae8076 completed March 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7cf498af4819085d494f85adf0825 completed March 4, 2026, 6:20 a.m.
Created at: March 1, 2026, 7:36 p.m.