Triple

T4414436
Position Surface form Disambiguated ID Type / Status
Subject Diane Sawyer E94929 entity
Predicate givenName P17 FINISHED
Object Lila E52031 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: Lila | Statement: [Diane Sawyer, givenName, Lila]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lila
Context triple: [Diane Sawyer, givenName, Lila]
  • A. 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.
  • B. Lilia
    Lilia is a feminine given name, often considered a variant of Lily and associated with the elegance and symbolism of the lily flower.
  • C. Lily
    Lily is a pivotal character in the psychological thriller film "Black Swan," serving as a seductive and enigmatic rival whose presence intensifies the protagonist's descent into paranoia and self-destruction.
  • D. Lily chosen
    Lily is a feminine given name of English origin commonly associated with the lily flower and symbolizing purity and beauty.
  • E. Lillie
    Lillie is the given name of Lillie Hitchcock Coit, a famed 19th-century San Francisco socialite and patron associated with the city’s firefighting history.
  • 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_69b34539638c8190abfea3eb29425210 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b354e940d48190b49cca6796d60de4 completed March 13, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5f617012481908b8f1a9a1bc5efaf completed March 14, 2026, 11:58 p.m.
Created at: March 12, 2026, 11:29 p.m.