Triple
T10534946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xpujil |
E248538
|
entity |
| Predicate | hasNearbyAirportType |
P9678
|
FINISHED |
| Object | small airstrip |
—
|
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: small airstrip | Statement: [Xpujil, hasNearbyAirportType, small airstrip]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyAirportType Context triple: [Xpujil, hasNearbyAirportType, small airstrip]
-
A.
nearbyAirportAccess
Indicates that an entity has convenient access to an airport located within a short distance or travel time.
-
B.
hasNearbyGeneralAviationAirport
chosen
Indicates that an entity is located close to a general aviation airport, such that the airport can reasonably serve it for non-commercial or private air traffic.
-
C.
isLocatedAtAirportType
Indicates that one entity is situated at, or associated with, an airport of a specified type (e.g., international, regional, military).
-
D.
nearestAirport
Indicates that one airport is the closest in distance to a given location or entity compared to all other airports.
-
E.
hasAirportWithinJurisdiction
Indicates that a governing authority or administrative region has legal or administrative control over an airport located within its boundaries.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a1a754c8190b53f2df28a1dfef1 |
completed | April 7, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69d4fb9729288190a0149f127acd7ae3 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:31 p.m.