Triple

T8376008
Position Surface form Disambiguated ID Type / Status
Subject Tabitha Grant E197576 entity
Predicate notableRelative P367 FINISHED
Object Tinglan Hong E731274 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: Tinglan Hong | Statement: [Tabitha Grant, notableRelative, Tinglan Hong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tinglan Hong
Context triple: [Tabitha Grant, notableRelative, Tinglan Hong]
  • A. Tinglan Hong chosen
    Tinglan Hong is a Chinese-born former London restaurant hostess best known as the mother of Hugh Grant’s daughter Tabitha and son Felix.
  • B. Cheng Hong
    Cheng Hong is a Chinese scholar and professor of English literature, best known publicly as the wife of former Chinese premier Li Keqiang.
  • C. Wu Hong
    Wu Hong is a Chinese art historian and curator renowned for his scholarship on traditional and contemporary Chinese art.
  • D. Ben Ling
    Ben Ling is a prominent technology investor and entrepreneur known for his leadership roles at major tech companies and his work as a general partner at venture capital firms.
  • E. Langche Zeng
    Langche Zeng is a political scientist and quantitative methodologist known for his collaborative work with Gary King on statistical methods in social science research.
  • 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_69ca82f64c188190af4e1608036b865d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80bf6b8081909b98762b1f900bef completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d14baf88190bc260efda7d0fc0d completed April 2, 2026, 7:39 a.m.
Created at: March 30, 2026, 6:01 p.m.