Triple

T29475287
Position Surface form Disambiguated ID Type / Status
Subject Chungking Express E747632 entity
Predicate producer P490 FINISHED
Object Chan Yi-kan
Chan Yi-kan is a Hong Kong film producer best known for his work on Wong Kar-wai’s acclaimed 1994 drama "Chungking Express."
E1878200 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: Chan Yi-kan | Statement: [Chungking Express, producer, Chan Yi-kan]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Chan Yi-kan
Triple: [Chungking Express, producer, Chan Yi-kan]
Generated description
Chan Yi-kan is a Hong Kong film producer best known for his work on Wong Kar-wai’s acclaimed 1994 drama "Chungking Express."

Provenance (5 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_69f0bd42cf308190bb01b20bc5b7c2d0 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66bd3e30c8190845285003677585d completed May 2, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a267e9c276881909e9b83efd97e145f completed June 8, 2026, 8:34 a.m.
NEDg Description generation batch_6a268282fad08190a2910d0526965dfc completed June 8, 2026, 8:51 a.m.
NED2 Entity disambiguation (via description) batch_6a26867701108190b9ab9434ee82344e completed June 8, 2026, 9:08 a.m.
Created at: April 28, 2026, 3:59 p.m.