Triple
T17749462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curse of the Golden Flower |
E443074
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Jay Chou |
—
|
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: Jay Chou | Statement: [Curse of the Golden Flower, starring, Jay Chou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jay Chou Context triple: [Curse of the Golden Flower, starring, Jay Chou]
-
A.
Jay Chou
chosen
Jay Chou is a Taiwanese singer-songwriter, producer, and actor widely regarded as a pioneer of Mandopop who blends Western and Chinese musical styles.
-
B.
He Chao
He Chao is a Chinese diver who has competed internationally, including at the Olympic Games and World Championships.
-
C.
Li Guo
Li Guo is a mathematician known for his significant contributions to the theory and applications of Rota–Baxter algebras.
-
D.
Mark Liu
Mark Liu is a prominent Taiwanese semiconductor executive best known as the former chairman of Taiwan Semiconductor Manufacturing Company (TSMC), a leading global chip foundry.
-
E.
Eason Chan
Eason Chan is a highly acclaimed Hong Kong singer and actor, widely recognized as one of the leading figures in contemporary Cantopop.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48418c0188190beb31809b40e4648 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 10:10 a.m.