Triple
T12524746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samastipur Junction |
E299405
|
entity |
| Predicate | hasDrinkingWaterFacilities |
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: [Samastipur Junction, hasDrinkingWaterFacilities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDrinkingWaterFacilities Context triple: [Samastipur Junction, hasDrinkingWaterFacilities, yes]
-
A.
hasAblutionFacilities
Indicates that an entity provides or is equipped with facilities for performing ablution or ritual washing.
-
B.
hasWaterResourceType
Indicates that an entity is associated with a specific type or category of water resource.
-
C.
hasWaterManagementStructure
Indicates that one entity possesses, contains, or is associated with a built feature used to control, store, convey, or manage water.
-
D.
hasNearbyWaterInfrastructure
Indicates that a location or entity is situated close to water-related infrastructure such as pipes, treatment facilities, or distribution systems.
-
E.
hasWaterUse
Indicates a relationship where one entity utilizes or consumes water for a particular purpose, process, or function.
- F. None of above. chosen
Provenance (4 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d95f5148948190946a575d812b329d |
completed | April 10, 2026, 8:36 p.m. |
Created at: April 8, 2026, 9:57 p.m.