Triple

T17025685
Position Surface form Disambiguated ID Type / Status
Subject Wheels on Meals E413057 entity
Predicate writer P1360 FINISHED
Object Edward Tang NE NERFINISHED

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: Edward Tang | Statement: [Wheels on Meals, writer, Edward Tang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edward Tang
Context triple: [Wheels on Meals, writer, Edward Tang]
  • A. Edward Tang chosen
    Edward Tang is a Hong Kong screenwriter best known for his work on Jackie Chan–led action films, including the influential "Police Story" series.
  • B. Daren Tang
    Daren Tang is a Singaporean lawyer and intellectual property expert who serves as the Director General of the World Intellectual Property Organization (WIPO).
  • C. Edward Wang
    Edward Wang is an entrepreneur best known as a founder of the virtualization and cloud computing company VMware.
  • D. Stephen Wang
    Stephen Wang is an entrepreneur best known as a co-founder of the film and television review aggregation website Rotten Tomatoes.
  • E. Charles Huang
    Charles Huang is an American entrepreneur best known as the co-founder of RedOctane, the company behind the hit video game franchise Guitar Hero.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d5d46a5081908bc5681621dd8534 completed April 18, 2026, 7:04 p.m.
Created at: April 10, 2026, 5:33 a.m.