Triple
T34752329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ambootia Tea Estate |
E1001815
|
entity |
| Predicate | teaGradeProduced |
P53105
|
FINISHED |
| Object | FTGFOP (Fine Tippy Golden Flowery Orange Pekoe) |
—
|
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: FTGFOP (Fine Tippy Golden Flowery Orange Pekoe) | Statement: [Ambootia Tea Estate, teaGradeProduced, FTGFOP (Fine Tippy Golden Flowery Orange Pekoe)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teaGradeProduced Context triple: [Ambootia Tea Estate, teaGradeProduced, FTGFOP (Fine Tippy Golden Flowery Orange Pekoe)]
-
A.
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.
-
B.
teaGradeVariation
Indicates differences or changes in the quality or grade levels assigned to tea.
-
C.
teaType
chosen
Indicates the specific variety or category of tea associated with an entity.
-
D.
coffeeProfile
Indicates the characteristic flavor, aroma, and strength attributes that define a particular coffee.
-
E.
teaBrand
Indicates that one entity is a brand or producer associated with a particular type or product line of tea for the other entity.
- 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_69f76db0fb30819096709d43f9a1f45f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.