Triple
T18859665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhou Baozhong |
E461275
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Baozhong |
—
|
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: Baozhong | Statement: [Zhou Baozhong, givenName, Baozhong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baozhong Context triple: [Zhou Baozhong, givenName, Baozhong]
-
A.
Baozhong tea
chosen
Baozhong tea is a lightly oxidized, floral Taiwanese oolong tea prized for its delicate aroma and smooth, refreshing taste.
-
B.
Da Hong Pao
Da Hong Pao is a legendary and highly prized Chinese oolong tea, renowned for its rich, roasted flavor and origin in the rocky cliffs of the Wuyi Mountains.
-
C.
Tieguanyin tea
Tieguanyin tea is a famous Chinese oolong tea variety renowned for its floral aroma, rich flavor, and origins in Fujian Province.
-
D.
Longjing tea
Longjing tea is a famous high-quality Chinese green tea, renowned for its flat, jade-green leaves and delicate, nutty flavor, traditionally produced near Hangzhou in Zhejiang province.
-
E.
Lu’an Guapian tea
Lu’an Guapian tea is a famous Chinese green tea from Lu’an in Anhui Province, renowned for its flat, melon-seed-shaped leaves and rich, mellow flavor.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c05fb800819098951ec134a1fa2a |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 10, 2026, 11:57 a.m.