Triple

T9802570
Position Surface form Disambiguated ID Type / Status
Subject Chow Yun-fat as the Monk E237874 entity
Predicate associatedWith P37 FINISHED
Object Kar E240310 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: Kar | Statement: [Chow Yun-fat as the Monk, associatedWith, Kar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kar
Context triple: [Chow Yun-fat as the Monk, associatedWith, Kar]
  • A. Kar chosen
    Kar is the young, streetwise pickpocket chosen as the reluctant successor to a mystical protector in the action film "Bulletproof Monk."
  • B. Ka
    Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
  • C. Ka
    Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
  • D. Kat
    Kat is a given name, typically used as a shortened or informal form of Kathleen or Katherine.
  • E. Ke
    Ke is the given name of Ke Huy Quan, the Vietnamese-American actor and former child star known for roles in films like "Indiana Jones and the Temple of Doom," "The Goonies," and "Everything Everywhere All at Once."
  • 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_69ca84dd4608819097ff4ed00feca280 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda62b41048190bcef70a7591830c6 completed April 1, 2026, 11:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1e410df4081909e1b03f46e9ca42a completed April 5, 2026, 4:24 a.m.
Created at: March 30, 2026, 8:29 p.m.