Triple

T6092941
Position Surface form Disambiguated ID Type / Status
Subject Sylvia Fedoruk E135810 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 Fedoruk, givenName, Sylvia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sylvia
Context triple: [Sylvia Fedoruk, givenName, 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’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.
  • D. 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.
  • E. Lila
    Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
  • 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_69c0087cd3c48190b459848c72d84eb1 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c057ac8c7481909fb22cf157be45ce completed March 22, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c125365a7481909e40d01c2d3590aa completed March 23, 2026, 11:34 a.m.
Created at: March 22, 2026, 4:12 p.m.