Triple
T28169585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piedras Negras International Airport |
E715418
|
entity |
| Predicate | nearBorderCity |
P80694
|
FINISHED |
| Object | Eagle Pass, Texas |
—
|
NE NERFINISHED |
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: Eagle Pass, Texas | Statement: [Piedras Negras International Airport, nearBorderCity, Eagle Pass, Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearBorderCity Context triple: [Piedras Negras International Airport, nearBorderCity, Eagle Pass, Texas]
-
A.
nearBorderBetween
Indicates that something is located close to the dividing line or boundary shared between two adjacent areas or regions.
-
B.
nearestCityTo
Indicates that one city is the closest in distance to a given location or entity compared to all other cities.
-
C.
nearStateBorderWith
Indicates that one entity is located close to the state border shared with another specified state or region.
-
D.
hasNearbyCityArea
chosen
Indicates that one area is geographically close to or adjacent to a city area.
-
E.
nearProvince
Indicates that one province is geographically close to or bordering another province.
- 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_69efd6b340f0819095680e15dcdc1830 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: April 27, 2026, 10:11 p.m.