Triple
T24888157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buchanan Field Airport |
E622914
|
entity |
| Predicate | located in metropolitan area |
P114292
|
FINISHED |
| Object | San Francisco Bay Area |
—
|
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: San Francisco Bay Area | Statement: [Buchanan Field Airport, located in metropolitan area, San Francisco Bay Area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: located in metropolitan area Context triple: [Buchanan Field Airport, located in metropolitan area, San Francisco Bay Area]
-
A.
locatedNearMetropolitanArea
Indicates that one entity is situated in close geographic proximity to a metropolitan (urban) area.
-
B.
operatesInMetropolitanArea
Indicates that an entity conducts its activities or provides its services within a specified metropolitan area.
-
C.
partOfMetropolitanArea
Indicates that one place is included within and belongs to the larger metropolitan area of another place.
-
D.
isWithinMetroArea
chosen
Indicates that one location lies inside the geographic boundaries of a specified metropolitan area.
-
E.
includesMajorMetropolitanArea
Indicates that one entity geographically contains or encompasses a major metropolitan area 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_69e2fac4aa848190b3446a3922cec150 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 18, 2026, 5:25 a.m.