Triple
T32207831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rishikesh railway station |
E822718
|
entity |
| Predicate | servesNearbyDestination |
P61362
|
FINISHED |
| Object | Laxman Jhula area |
—
|
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: Laxman Jhula area | Statement: [Rishikesh railway station, servesNearbyDestination, Laxman Jhula area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesNearbyDestination Context triple: [Rishikesh railway station, servesNearbyDestination, Laxman Jhula area]
-
A.
operatesNear
Indicates that one entity performs its activities or functions in close physical proximity to another entity.
-
B.
servedNearbyEstates
Indicates that an entity provided services or assistance to estates located in its immediate geographic vicinity.
-
C.
nearbyTo
chosen
Indicates that one entity is located close in distance or position to another entity.
-
D.
nearbyUse
Indicates that one entity uses or operates another entity that is located nearby or in close physical proximity.
-
E.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
- 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_69f3490a3bec819097bc58d4731b9d08 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff1d85441c8190931e758685a269f7 |
completed | May 9, 2026, 11:41 a.m. |
| PD | Predicate disambiguation | batch_69ff1d186cc48190b315c61e23de6551 |
completed | May 9, 2026, 11:40 a.m. |
Created at: May 1, 2026, 12:37 a.m.