Triple
T17935778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cattaraugus County-Olean Airport |
E448461
|
entity |
| Predicate | distanceFromOlean (miles) |
P129780
|
FINISHED |
| Object | approximately 10 |
—
|
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: approximately 10 | Statement: [Cattaraugus County-Olean Airport, distanceFromOlean (miles), approximately 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromOlean (miles) Context triple: [Cattaraugus County-Olean Airport, distanceFromOlean (miles), approximately 10]
-
A.
distanceToSyracuse
Indicates the spatial distance between a given entity’s location and the location of Syracuse.
-
B.
distanceToPoughkeepsie
Indicates the spatial distance between a given entity and the location of Poughkeepsie.
-
C.
distanceToCantonInMiles
Indicates the physical separation between an entity and a specified canton, measured in miles.
-
D.
distanceToColumbus
Indicates the spatial distance between a given entity and the location of Columbus.
-
E.
distanceFromHanaTown (miles)
Indicates the number of miles separating a given place or entity from Hana Town.
- F. None of above. chosen
Provenance (4 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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a55536e0819083dcfc4be71d447a |
completed | April 19, 2026, 9:50 a.m. |
| PD | Predicate disambiguation | batch_69e3f8e713d481908b4a126258c18b63 |
completed | April 18, 2026, 9:34 p.m. |
| PDg | Predicate description generation | batch_69e42d8d68288190a05dc5d7803cf823 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:21 a.m.