Triple

T6939295
Position Surface form Disambiguated ID Type / Status
Subject Joan S. Birman E160631 entity
Predicate middleName P143 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: [Joan S. Birman, middleName, Sylvia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sylvia
Context triple: [Joan S. Birman, middleName, Sylvia]
  • A. Sylvia chosen
    Sylvia is a feminine given name of Latin origin meaning "from the forest" or "of the woods."
  • B. 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.
  • 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’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.
  • E. Sylvia’s Mother
    "Sylvia’s Mother" is a country-pop song, popularized by Dr. Hook & the Medicine Show, that tells a bittersweet story of lost love through a one-sided phone call.
  • 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_69c6884f3db4819080ad65da69386206 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da641ce08190a133c9ba4977755d completed March 27, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7515880948190970cadd7adeda435 completed March 28, 2026, 3:56 a.m.
Created at: March 27, 2026, 2:28 p.m.