Triple

T12228697
Position Surface form Disambiguated ID Type / Status
Subject John Lee Ka-chiu E291418 entity
Predicate spouse P13 FINISHED
Object Janet Lam E291418 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: Janet Lam | Statement: [John Lee Ka-chiu, spouse, Janet Lam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Janet Lam
Context triple: [John Lee Ka-chiu, spouse, Janet Lam]
  • A. Janet Lam chosen
    Janet Lam is known as the wife of John Lee Ka-chiu, the Chief Executive of Hong Kong.
  • B. Eileen Loo
    Eileen Loo was the wife of renowned Chinese-American architect I. M. Pei and a supportive partner throughout his celebrated career.
  • C. Margaret Chung
    Margaret Chung was a pioneering Chinese American physician and surgeon, widely regarded as the first Chinese American woman doctor in the United States and known for her influential role in supporting U.S. military personnel during World War II.
  • D. Karen Kwan
    Karen Kwan is an American figure skater and the older sister of Olympic medalist Michelle Kwan.
  • E. Rachel Fong
    Rachel Fong is a researcher in machine learning and reinforcement learning, known for her work on the Hindsight Experience Replay technique.
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91ca34fe88190900c8791c70948b7 completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60aab4a70819099856b990e3a8a1b completed May 2, 2026, 2:31 p.m.
Created at: April 8, 2026, 9:51 p.m.