Triple
T7640682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tea City of India |
E172995
|
entity |
| Predicate | partOfCountryTeaBelt |
P65771
|
FINISHED |
| Object | Indian tea-growing region |
—
|
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: Indian tea-growing region | Statement: [Tea City of India, partOfCountryTeaBelt, Indian tea-growing region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfCountryTeaBelt Context triple: [Tea City of India, partOfCountryTeaBelt, Indian tea-growing region]
-
A.
countryPortionIn
Indicates that a specific part or region is located within the boundaries of a particular country.
-
B.
partOfCountrySubdivision
Indicates that one geographic or administrative unit is contained within and forms a component part of a larger country subdivision.
-
C.
regionCountrySide
Indicates that a region is located in or associated with the countryside or rural area of a country.
-
D.
partOfTerritory
chosen
Indicates that one geographic or administrative area is contained within, and forms a constituent portion of, another territory.
-
E.
regionallyAssociatedWith
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6facd9dec8190ab3af9cdde9992e6 |
completed | March 27, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e8cadc8190b7977fcd213954dd |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:57 p.m.