Triple

T21348166
Position Surface form Disambiguated ID Type / Status
Subject Sylvia Neary E526397 entity
Predicate givenName P17 FINISHED
Object Sylvia NE NERFINISHED

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: Sylvia | Statement: [Sylvia Neary, givenName, Sylvia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sylvia
Context triple: [Sylvia Neary, givenName, Sylvia]
  • A. Sylvia
    Sylvia is a key character in the film "The Truman Show," a woman who tries to reveal the truth to Truman about his manufactured reality and becomes his inspiration to escape.
  • B. Sylvia chosen
    Sylvia is a feminine given name of Latin origin meaning "from the forest" or "of the woods."
  • C. Sylvia
    Sylvia is a central female character in George Farquhar’s Restoration comedy "The Recruiting Officer," known for her wit, disguise, and critique of gender and social norms.
  • D. Sylvia
    Sylvia is a character in the film "Birdman," known as the ex-wife of the troubled actor Riggan Thomson.
  • E. Sylvia
    "Sylvia" is a stage play best known from its Broadway revival starring Annaleigh Ashford as a dog who upends her owners’ lives with her exuberant personality.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51cd5cc81909ac1187971e8a8ad completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee5baab4e081908916a289c607cf3a completed April 26, 2026, 6:38 p.m.
Created at: April 16, 2026, 5:01 p.m.