Triple
T27646898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nilgiri tea |
E696735
|
entity |
| Predicate | belongsToTeaRegion |
P62960
|
FINISHED |
| Object | South Indian tea region |
—
|
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: South Indian tea region | Statement: [Nilgiri tea, belongsToTeaRegion, South Indian tea region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToTeaRegion Context triple: [Nilgiri tea, belongsToTeaRegion, South Indian tea region]
-
A.
teaProductionRegion
chosen
Indicates the region or area where tea is produced or cultivated.
-
B.
partOfCoffeeRegion
Indicates that one entity is a subregion or component area within a larger coffee-producing region.
-
C.
connectsToAgriculturalRegion
Indicates a relationship where something is linked or associated with an agricultural region, such as through proximity, infrastructure, or functional interaction.
-
D.
coffeeSourcingRegion
Indicates the geographic region from which the coffee was originally sourced or obtained.
-
E.
cultivatedBy
Indicates that something (such as land, crops, or plants) is grown, tended, or developed through the efforts or care of a particular agent.
- 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_69ef590abd3c8190834d0193bde12007 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f7c29e1b848190b945c6c6120a5330 |
completed | May 3, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
Created at: April 27, 2026, 2:29 p.m.