Triple
T3135200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Fe Regional Airport |
E65509
|
entity |
| Predicate | hasPushpinMapCaption |
P44061
|
FINISHED |
| Object | Location of airport in New Mexico |
—
|
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: Location of airport in New Mexico | Statement: [Santa Fe Regional Airport, hasPushpinMapCaption, Location of airport in New Mexico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPushpinMapCaption Context triple: [Santa Fe Regional Airport, hasPushpinMapCaption, Location of airport in New Mexico]
-
A.
mapCaption
chosen
Indicates that the value is a textual caption or label describing the associated map.
-
B.
mapLabel
Indicates that a label or name is assigned to a map or mapped entity for identification or display.
-
C.
pushpinMapCountry
Indicates the country whose map is used as the background or reference area for placing a pushpin-style location marker.
-
D.
mapNumber
Indicates a correspondence where each element in one set or collection is assigned a specific numeric value in another set or domain.
-
E.
mapsFrom
Indicates that one entity is derived, transformed, or constructed based on data, structure, or content originating from another entity.
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5637de0819089393429c4017298 |
completed | March 8, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69ad9df840088190a26a1516f4c1f056 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:05 p.m.