Triple
T31253781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Da Hong Pao |
E796902
|
entity |
| Predicate | teaProcessingStyle |
P171503
|
FINISHED |
| Object | partially oxidized |
—
|
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: partially oxidized | Statement: [Da Hong Pao, teaProcessingStyle, partially oxidized]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teaProcessingStyle Context triple: [Da Hong Pao, teaProcessingStyle, partially oxidized]
-
A.
coffeeProcessingMethods
Indicates the methods or techniques used to transform raw coffee cherries or beans into a consumable coffee product.
-
B.
teaType
Indicates the specific variety or category of tea associated with an entity.
-
C.
teaProduct
Indicates that something is a product related to tea, such as an item made from, flavored with, or intended for preparing or consuming tea.
-
D.
teaCulture
Indicates the relationship in which practices, rituals, and social norms surrounding the preparation and consumption of tea are shared, expressed, or maintained.
-
E.
teaSeason
Indicates the season or time of year during which tea is typically grown, harvested, or most commonly consumed.
- F. None of above. chosen
Provenance (4 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69edae2448190925ce701c8792c52 |
completed | May 3, 2026, 1:03 a.m. |
Created at: April 29, 2026, 9:12 p.m.