Triple
T2898820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guanajuato International Airport |
E62605
|
entity |
| Predicate | distanceToCityCenterReference |
P1299
|
FINISHED |
| Object | León city center |
—
|
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: León city center | Statement: [Guanajuato International Airport, distanceToCityCenterReference, León city center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCityCenterReference Context triple: [Guanajuato International Airport, distanceToCityCenterReference, León city center]
-
A.
directionFromCityCenter
Indicates the compass direction in which one location lies relative to the city center.
-
B.
directionFromCityCentre
Indicates the compass direction in which one location lies relative to the city centre.
-
C.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
D.
districtHeadquartersDistance
Indicates the distance between a place and its corresponding district headquarters.
-
E.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe0ad7bbc8190822738baa6935b74 |
completed | March 7, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69abdd17bcdc8190aa47274a50ba4ad4 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:10 p.m.