Triple

T2498345
Position Surface form Disambiguated ID Type / Status
Subject Laura Linney E52403 entity
Predicate givenName P17 FINISHED
Object Laura E142585 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: Laura | Statement: [Laura Linney, givenName, Laura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laura
Context triple: [Laura Linney, givenName, Laura]
  • A. Laura chosen
    Laura is a feminine given name of Latin origin, commonly used in many languages and cultures.
  • B. Laura
    Laura is a classic 1944 American film noir mystery celebrated for its sophisticated storytelling, atmospheric cinematography, and iconic score.
  • C. Lisa
    Lisa is a central character in the science fiction adventure film "Zathura: A Space Adventure," where she becomes unwittingly involved in her younger brothers' perilous journey through outer space.
  • D. Jessica
    Jessica is a kind-hearted schoolteacher who becomes Mrs. Claus in the classic stop-motion Christmas special "Santa Claus Is Comin' to Town."
  • E. Jessica
    Jessica Barth is an American actress best known for her comedic role as Tami-Lynn in the "Ted" film series.
  • 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_69ab4957b3a88190adf968ae0c1b931c completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1ae9040819091b3ca5b98659e99 completed March 7, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f9be594819099a03a2784691124 completed March 9, 2026, 7:29 p.m.
Created at: March 6, 2026, 9:46 p.m.