Triple

T11748108
Position Surface form Disambiguated ID Type / Status
Subject Sylvia Woods E279335 entity
Predicate givenName P17 FINISHED
Object Sylvia E30938 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: Sylvia | Statement: [Sylvia Woods, givenName, Sylvia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sylvia
Context triple: [Sylvia Woods, 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 biographical drama film about poet Sylvia Plath, focusing on her turbulent marriage to Ted Hughes and her creative and emotional struggles.
  • D. 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.
  • E. Sylvia’s
    Sylvia’s is a famed soul food restaurant in Harlem, New York City, renowned for its Southern cuisine and cultural significance in the neighborhood.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a50763a081908597da118bd0a64e completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f0902f8c448190a71512353788ef09 completed April 28, 2026, 10:47 a.m.
Created at: April 8, 2026, 9:41 p.m.