Triple
T22229956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhang Huiwen |
E549439
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Zhang Huiwen |
—
|
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: Zhang Huiwen | Statement: [Zhang Huiwen, name, Zhang Huiwen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zhang Huiwen Context triple: [Zhang Huiwen, name, Zhang Huiwen]
-
A.
Zhang Huiwen
chosen
Zhang Huiwen is a Chinese actress best known for her breakout role in Zhang Yimou’s film "Coming Home," which brought her widespread recognition.
-
B.
Huang Huidan
Huang Huidan is a Chinese artistic gymnast best known for her world-class performances on the uneven bars, including winning the world title on the event.
-
C.
Zhang Huike
Zhang Huike is a Chinese actor best known for his breakout role as the schoolboy protagonist in Zhang Yimou’s acclaimed film "Not One Less."
-
D.
Zhao Huanyu
Zhao Huanyu is an actor known for appearing in the Chinese film "Special ID."
-
E.
Wang Qianyuan
Wang Qianyuan is a Chinese actor known for his acclaimed performances in both film and television, including roles in major historical and action dramas.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf173308190a3d21bfc59b39728 |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:37 p.m.