Triple
T23800844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tikamgarh railway station |
E588666
|
entity |
| Predicate | hasWaterFacilities |
P105704
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tikamgarh railway station, hasWaterFacilities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterFacilities Context triple: [Tikamgarh railway station, hasWaterFacilities, yes]
-
A.
hasDrinkingWaterFacilities
chosen
Indicates that a place or facility provides access to safe drinking water sources or infrastructure for people to use.
-
B.
hasWaterServiceFrom
Indicates that one entity receives its water supply or water-related services from another entity.
-
C.
hasNearbyWaterInfrastructure
Indicates that a location or entity is situated close to water-related infrastructure such as pipes, treatment facilities, or distribution systems.
-
D.
hasWaterFeatures
Indicates that an entity includes or is associated with water-related elements such as fountains, ponds, streams, or similar features.
-
E.
hasWaterManagementStructure
Indicates that one entity possesses, contains, or is associated with a built feature used to control, store, convey, or manage water.
- 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_69e25d15db58819092ac1e6791696fd9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c6e0814081908a81e1ede05ab810 |
completed | April 29, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:53 p.m.