Triple
T25231579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen’s Bath (Hampi) |
E632230
|
entity |
| Predicate | hasWaterSupplyFeature |
P64067
|
FINISHED |
| Object | inlet channels |
—
|
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: inlet channels | Statement: [Queen’s Bath (Hampi), hasWaterSupplyFeature, inlet channels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterSupplyFeature Context triple: [Queen’s Bath (Hampi), hasWaterSupplyFeature, inlet channels]
-
A.
hasWaterResourceType
Indicates that an entity is associated with a specific type or category of water resource.
-
B.
hasWaterFeatures
chosen
Indicates that an entity includes or is associated with water-related elements such as fountains, ponds, streams, or similar features.
-
C.
hasDrinkingWaterFacilities
Indicates that a place or facility provides access to safe drinking water sources or infrastructure for people to use.
-
D.
hasWaterResourceRole
Indicates that an entity participates in a water-related resource context with a specified functional role (e.g., source, user, manager, or regulator of water resources).
-
E.
hasWaterServiceFrom
Indicates that one entity receives its water supply or water-related services from another entity.
- 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_69e75a8ec5f88190b9eba06ae42b413a |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 21, 2026, 1:06 p.m.