Triple
T2271944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Four Corners Monument (Arizona corner) |
E50678
|
entity |
| Predicate | hasNearbyServices |
P5648
|
FINISHED |
| Object | vendor stalls |
—
|
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: vendor stalls | Statement: [Four Corners Monument (Arizona corner), hasNearbyServices, vendor stalls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyServices Context triple: [Four Corners Monument (Arizona corner), hasNearbyServices, vendor stalls]
-
A.
hasNearbyMode
Indicates that one entity has another entity located close enough to be considered in its immediate vicinity or surrounding area.
-
B.
hasNearbyFunction
Indicates that one entity has another entity located close by that serves a related or supportive function.
-
C.
hasNearbyFacility
chosen
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
D.
hasNearbyBase
Indicates that one entity has a base or facility located in close physical proximity to another entity or location.
-
E.
hasNearbySquare
Indicates that one entity has at least one square-shaped entity located close to it in space.
- 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc39c6ff0819081a07696f1c29990 |
completed | March 7, 2026, 6:20 a.m. |
| PD | Predicate disambiguation | batch_69abbdb7719081909143efa8f48df4e4 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.