Triple

T4033227
Position Surface form Disambiguated ID Type / Status
Subject Alice Through the Looking Glass (2016 film) E83761 entity
Predicate featuresCharacter P626 FINISHED
Object Caterpillar E285260 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: Caterpillar | Statement: [Alice Through the Looking Glass (2016 film), featuresCharacter, Caterpillar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caterpillar
Context triple: [Alice Through the Looking Glass (2016 film), featuresCharacter, Caterpillar]
  • A. Caterpillar chosen
    The Caterpillar is a wise, enigmatic blue insect who serves as a cryptic advisor to Alice in Tim Burton’s 2010 fantasy film "Alice in Wonderland."
  • B. Caterpillar
    Caterpillar is a leading American manufacturer of construction and mining equipment, diesel and natural gas engines, industrial gas turbines, and locomotives.
  • C. Toro
    Toro is the bull mascot representing California State University, Dominguez Hills at its athletic events and campus activities.
  • D. Toro
    Toro is the traditional nickname of Torino F.C., a historic Italian football club based in Turin.
  • E. Toro
    Toro is the official bull-themed mascot of the NFL's Houston Texans, known for entertaining fans at games and team events.
  • 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_69aed92e29ac819080f7a98b594fec05 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb108fc0819080c8f41da2e558e0 completed March 9, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5563e11708190abc9ba55b1be43a5 completed March 14, 2026, 12:36 p.m.
Created at: March 9, 2026, 3:36 p.m.