Triple
T26140336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thuraiyur |
E659497
|
entity |
| Predicate | hasAgricultureType |
P137337
|
FINISHED |
| Object | Paddy cultivation 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: Paddy cultivation region | Statement: [Thuraiyur, hasAgricultureType, Paddy cultivation region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgricultureType Context triple: [Thuraiyur, hasAgricultureType, Paddy cultivation region]
-
A.
hasAgriculturalType
chosen
Indicates that an entity is associated with or classified by a specific type or category of agriculture.
-
B.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
C.
hasAgriculturalProduction
Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
-
D.
isCultivatedAs
Indicates that one entity is intentionally grown, tended, or produced by another as a crop, resource, or cultivated organism.
-
E.
hasAgriculturalModel
Indicates that one entity possesses, uses, or is associated with a specific agricultural model (such as a framework, simulation, or methodology for agricultural processes).
- 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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f60be435b48190a389ebb5a4537a16 |
completed | May 2, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69f5b0021da88190bdd4cf2698c23edf |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 26, 2026, 8:19 p.m.