Triple
T9414832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tinsukia |
E226989
|
entity |
| Predicate | hasNearbyTeaGrowingArea |
P62960
|
FINISHED |
| Object | Tinsukia district tea gardens |
—
|
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: Tinsukia district tea gardens | Statement: [Tinsukia, hasNearbyTeaGrowingArea, Tinsukia district tea gardens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyTeaGrowingArea Context triple: [Tinsukia, hasNearbyTeaGrowingArea, Tinsukia district tea gardens]
-
A.
teaProductionRegion
chosen
Indicates the region or area where tea is produced or cultivated.
-
B.
cultivatedBy
Indicates that something (such as land, crops, or plants) is grown, tended, or developed through the efforts or care of a particular agent.
-
C.
hasCultivationSite
Indicates that an entity possesses or is associated with a specific location where cultivation or growing activities take place.
-
D.
locatedInAgriculturalRegion
Indicates that an entity is situated within a region primarily characterized by agricultural activities or land use.
-
E.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68c7bd648190b17f082883c98239 |
completed | April 1, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69cca54c37f88190bddccf28e5fe5c84 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:47 p.m.