Triple

T901602
Position Surface form Disambiguated ID Type / Status
Subject Neil Young E19457 entity
Predicate spouse P13 FINISHED
Object Daryl Hannah E78247 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: Daryl Hannah | Statement: [Neil Young, spouse, Daryl Hannah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daryl Hannah
Context triple: [Neil Young, spouse, Daryl Hannah]
  • A. Daryl Hannah chosen
    Daryl Hannah is an American actress best known for her roles in films such as "Splash," "Blade Runner," and "Kill Bill."
  • B. Tyne Daly
    Tyne Daly is an American actress acclaimed for her powerful performances in television dramas, film, and theater, including her iconic role in the series "Cagney & Lacey."
  • C. Alexandra Hedison
    Alexandra Hedison is an American photographer, director, and former actress known for her contemporary art photography and her work on the television series "The L Word."
  • D. Liv Tyler
    Liv Tyler is an American actress and former model best known for her role as the elf Arwen in Peter Jackson’s The Lord of the Rings film trilogy.
  • E. Geena Davis
    Geena Davis is an American actress and producer known for her roles in films such as "Thelma & Louise," "A League of Their Own," and "The Fly," as well as for her advocacy for gender equality in media.
  • 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_69a4939e889c8190ac148b3ac1a7f90b completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad4412408190a6bf8fc7484a5781 completed March 1, 2026, 9:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69a826d6781081908a59c0263515bbc8 completed March 4, 2026, 12:34 p.m.
Created at: March 1, 2026, 7:39 p.m.