Triple
T11851475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amber |
E281917
|
entity |
| Predicate | proximityToAirport |
P94103
|
FINISHED |
| Object | near Jaipur International Airport |
—
|
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 International Airport | Statement: [Amber, proximityToAirport, near Jaipur International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proximityToAirport Context triple: [Amber, proximityToAirport, near Jaipur International Airport]
-
A.
distanceToAirport
Indicates the measured distance between a given location and the nearest or specified airport.
-
B.
nearestAirport
Indicates that one airport is the closest in distance to a given location or entity compared to all other airports.
-
C.
nearbyAirportRelationship
chosen
Indicates that one location has an airport situated close enough to serve it conveniently, establishing a nearby-airport relationship between the two.
-
D.
nearbyAirportAccess
Indicates that an entity has convenient access to an airport located within a short distance or travel time.
-
E.
proximityToLandmark
Indicates a spatial relationship where one entity is located near or close to a specified landmark.
- 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.