Triple
T11851476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amber |
E281917
|
entity |
| Predicate | proximityToRailwayStation |
P31869
|
FINISHED |
| Object | near Jaipur Junction railway station |
—
|
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: near Jaipur Junction railway station | Statement: [Amber, proximityToRailwayStation, near Jaipur Junction railway station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proximityToRailwayStation Context triple: [Amber, proximityToRailwayStation, near Jaipur Junction railway station]
-
A.
hasNearbyRailwayStation
chosen
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
-
B.
distanceFromStation
Indicates the measured spatial separation between an entity and a specified station.
-
C.
hasNearbyRailway
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
D.
nearestSuburbanRailwayStation
Indicates the relationship where a given place is associated with the suburban railway station that is geographically closest to it.
-
E.
nearestPassengerRailStation
Indicates that one entity is the closest passenger rail station in distance to 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65db52c8190a218736da17d0153 |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a2573dbc8190ab432e8e28fde6cc |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.