Triple
T6734846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narsinghpur |
E153726
|
entity |
| Predicate | hasNearbyIrrigationSource |
P31801
|
FINISHED |
| Object | Narmada River canals |
—
|
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: Narmada River canals | Statement: [Narsinghpur, hasNearbyIrrigationSource, Narmada River canals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyIrrigationSource Context triple: [Narsinghpur, hasNearbyIrrigationSource, Narmada River canals]
-
A.
hasIrrigation
Indicates that an entity is equipped with or benefits from an irrigation system supplying water.
-
B.
hasIrrigationArea
Indicates that an entity possesses or is associated with a specific area of land equipped or designated for irrigation.
-
C.
nearIrrigationProject
chosen
Indicates that one entity is located close to or in the vicinity of an irrigation project.
-
D.
hasNearbyWater
Indicates that one entity is located close to a body of water associated with or relevant to another entity.
-
E.
hasWaterUse
Indicates a relationship where one entity utilizes or consumes water for a particular purpose, process, or function.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d16ecbe08190b019d547f631a725 |
completed | March 27, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69c6d09067a0819087ed6c820f4699f8 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:09 p.m.