Triple

T29475592
Position Surface form Disambiguated ID Type / Status
Subject 2046 E747638 entity
Predicate cinematographyBy P1953 FINISHED
Object Kwan Pun-leung
Kwan Pun-leung is a Hong Kong cinematographer and filmmaker known for his visually expressive work on acclaimed art-house films, particularly in collaboration with director Wong Kar-wai.
E1890490 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: Kwan Pun-leung | Statement: [2046, cinematographyBy, Kwan Pun-leung]
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: Kwan Pun-leung
Triple: [2046, cinematographyBy, Kwan Pun-leung]
Generated description
Kwan Pun-leung is a Hong Kong cinematographer and filmmaker known for his visually expressive work on acclaimed art-house films, particularly in collaboration with director Wong Kar-wai.

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_6a26f1a85b6c8190abdb1f5c9cb2a79a completed June 8, 2026, 4:45 p.m.
NEDg Description generation batch_6a26f5850b44819097a4d2fbbf1a27aa completed June 8, 2026, 5:01 p.m.
NED2 Entity disambiguation (via description) batch_6a26f8484c6c819095f2718c50d70bdd completed June 8, 2026, 5:13 p.m.
Created at: April 28, 2026, 4 p.m.