Triple

T14599259
Position Surface form Disambiguated ID Type / Status
Subject Like Water for Chocolate E342658 entity
Predicate hasPart P35 FINISHED
Object Heat E404322 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: Heat | Statement: [Like Water for Chocolate, hasPart, Heat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heat
Context triple: [Like Water for Chocolate, hasPart, Heat]
  • A. Heat
    Heat is a 1995 crime thriller film directed by Michael Mann, renowned for its intense heist sequences and the iconic pairing of Al Pacino and Robert De Niro.
  • B. Heat chosen
    Heat is a chapter or section within the novel "Like Water for Chocolate" that focuses on themes of passion, desire, and emotional intensity.
  • C. Heat
    Heat is OpenStack’s orchestration service that automates the deployment and management of cloud infrastructure using template-based definitions.
  • D. Heat
    Heat is a 1972 American underground film directed by Paul Morrissey and produced by Andy Warhol, known for its satirical take on Hollywood and its place within the Warhol Factory film movement.
  • E. Heat
    Heat is a 1963 Soviet drama film directed by Larisa Shepitko, marking her acclaimed feature-length directorial debut.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb436d92881908fdf9267568feee2 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94ca0fec81908fb9c674f48a793b completed May 8, 2026, 7:46 a.m.
Created at: April 10, 2026, 1:25 a.m.