Triple
T3955137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huangshan Maofeng tea |
E84957
|
entity |
| Predicate | budCharacteristic |
P662
|
FINISHED |
| Object | abundant white hairs |
—
|
LITERAL 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: abundant white hairs | Statement: [Huangshan Maofeng tea, budCharacteristic, abundant white hairs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: budCharacteristic Context triple: [Huangshan Maofeng tea, budCharacteristic, abundant white hairs]
-
A.
brandAttribute
Indicates that a specific attribute or characteristic is associated with, or describes, a particular brand.
-
B.
neckCharacteristic
Indicates that an entity has a specific attribute, feature, or quality related to its neck.
-
C.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
D.
collarFeature
Indicates that one entity has a specific characteristic, detail, or attribute related to a collar.
-
E.
dressFeature
Indicates that a dress possesses or is characterized by a particular feature, attribute, or design element.
- F. None of above.
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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaa5afdc8190b709af2473d75d02 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8ed04e4819096bced8971cd888d |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:30 p.m.