Triple

T2139879
Position Surface form Disambiguated ID Type / Status
Subject Ratatouille E46736 entity
Predicate mainCharacter P1183 FINISHED
Object Linguini E232244 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: Linguini | Statement: [Ratatouille, mainCharacter, Linguini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linguini
Context triple: [Ratatouille, mainCharacter, Linguini]
  • A. Linguini chosen
    Linguini is the clumsy yet kind-hearted young chef from Disney-Pixar’s Ratatouille who secretly teams up with the rat Remy to create extraordinary dishes.
  • B. Meatballs
    Meatballs is a 1979 comedy film that helped establish Bill Murray as a major comedic star through his role as an irreverent summer camp counselor.
  • C. Alvito
    Alvito is a small Portuguese municipality in the Alentejo region, known for its historic castle and traditional rural landscape.
  • D. Alfredo
    Alfredo is a masculine given name, commonly used in Italian, Spanish, and Portuguese-speaking countries, derived from the name Alfred.
  • E. Prego
    Prego is a popular American brand of pasta sauces known for its thick, tomato-based varieties and wide range of flavors.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbe025d3c81908bcb33a7ff09eae8 completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51b37ce08190add9df46cc17ba89 completed March 9, 2026, 4:50 a.m.
Created at: March 4, 2026, 7:44 p.m.