Triple
T6309374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra Vista, Arizona |
E141460
|
entity |
| Predicate | regionFunction |
P32691
|
FINISHED |
| Object | regional shopping center for Cochise County |
—
|
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: regional shopping center for Cochise County | Statement: [Sierra Vista, Arizona, regionFunction, regional shopping center for Cochise County]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionFunction Context triple: [Sierra Vista, Arizona, regionFunction, regional shopping center for Cochise County]
-
A.
regionSub
Indicates that one region is a subregion or contained part of another, larger region.
-
B.
regionContext
chosen
Indicates the broader geographic or spatial setting within which an entity, event, or relationship is situated or interpreted.
-
C.
region1
Indicates that one entity is the first or primary region associated with, containing, or encompassing another entity.
-
D.
regionOfCity
Indicates that a specified area or district is a constituent part or subdivision of a particular city.
-
E.
regionException
Indicates an exception or exclusion to a rule, condition, or classification that applies specifically to a certain region or set of regions.
- 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_69c008d00efc8190a36c05b4b4a3bf4b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0647f13a4819095c4ce8c42c5d1fb |
completed | March 22, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:28 p.m.