Triple

T17904567
Position Surface form Disambiguated ID Type / Status
Subject Hong Chau E447668 entity
Predicate givenName P17 FINISHED
Object Hong 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: Hong | Statement: [Hong Chau, givenName, Hong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hong
Context triple: [Hong Chau, givenName, Hong]
  • A. Hong chosen
    Hong is a Chinese-origin surname shared by various notable individuals across different fields and regions.
  • B. Hong
    Hong is a prominent town in northeastern Nigeria that serves as a key cultural and administrative center for the Kilba people.
  • C. Tai Wai
    Tai Wai is a residential and transport hub area in Hong Kong’s New Territories, known for its major railway interchange and proximity to Sha Tin.
  • D. Hongkew
    Hongkew is a historic district of Shanghai that was once part of the foreign-controlled International Settlement and later became known for its diverse communities and wartime Jewish refugee population.
  • E. Hoi Ha
    Hoi Ha is a small coastal village and marine area in Hong Kong’s Sai Kung Peninsula, known for its clear waters, coral communities, and inclusion in the Hoi Ha Wan Marine Park.
  • 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_69d8b9f6d394819082a6d69fd1e23d2f completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49e9a9cfc8190879fc36dfdeb562b completed April 19, 2026, 9:21 a.m.
Created at: April 10, 2026, 10:19 a.m.