Triple

T2938642
Position Surface form Disambiguated ID Type / Status
Subject Vicky Cristina Barcelona E79329 entity
Predicate hasTitleCharacter P5716 FINISHED
Object Vicky E312155 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: Vicky | Statement: [Vicky Cristina Barcelona, hasTitleCharacter, Vicky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vicky
Context triple: [Vicky Cristina Barcelona, hasTitleCharacter, Vicky]
  • A. Vicky chosen
    Vicky is one of the two central female protagonists in Woody Allen's romantic drama film "Vicky Cristina Barcelona," whose contrasting personality and desires drive much of the story's emotional tension.
  • B. Vivian
    Vivian "Buster" Burey Marshall was a civil rights activist and the first wife of U.S. Supreme Court Justice Thurgood Marshall.
  • C. Vicky Bullett
    Vicky Bullett is a former American professional basketball player and Olympic gold medalist known for her standout career in the WNBA and with the U.S. national team.
  • D. Vinessa Shaw
    Vinessa Shaw is an American actress known for her roles in films such as "Hocus Pocus," "Eyes Wide Shut," and "The Hills Have Eyes."
  • E. Vanessa
    Vanessa is an English feminine given name that gained wider recognition through public figures such as Vanessa Trump.
  • 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_69ad8b0fbab081908f6a61567c045d8d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad986c1c0c8190a6a9f17082438cfd completed March 8, 2026, 3:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc7063dc819086ae9280d060313e completed March 11, 2026, 5:24 a.m.
Created at: March 8, 2026, 2:56 p.m.