Triple
T6834219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fan Chung |
E157409
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Fan Chung |
E157409
|
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: Fan Chung | Statement: [Fan Chung, name, Fan Chung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fan Chung Context triple: [Fan Chung, name, Fan Chung]
-
A.
Fan Chung
chosen
Fan Chung is a prominent mathematician known for her influential work in graph theory, combinatorics, and spectral graph theory.
-
B.
Rosalie Chiang
Rosalie Chiang is an American actress best known for voicing the main character, Meilin "Mei" Lee, in Pixar's animated film "Turning Red."
-
C.
Amy Chow
Amy Chow is an American artistic gymnast and Olympic gold medalist best known as a member of the 1996 U.S. women's "Magnificent Seven" team.
-
D.
Hong Chau
Hong Chau is an American actress acclaimed for her nuanced performances in film and television, including prominent roles in projects like "Downsizing," "The Whale," and various prestige TV series.
-
E.
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.
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d67936288190829fedc3729aadd8 |
completed | March 27, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723fd50c88190af005fd58ca0aee6 |
completed | March 28, 2026, 12:42 a.m. |
Created at: March 27, 2026, 2:18 p.m.