Triple
T10596835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shiprock, New Mexico |
E250135
|
entity |
| Predicate | proximityToStateBorder |
P61305
|
FINISHED |
| Object | near Arizona–New Mexico border |
—
|
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: near Arizona–New Mexico border | Statement: [Shiprock, New Mexico, proximityToStateBorder, near Arizona–New Mexico border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proximityToStateBorder Context triple: [Shiprock, New Mexico, proximityToStateBorder, near Arizona–New Mexico border]
-
A.
distanceToBorder
Indicates the measured or estimated spatial separation between a given entity or location and the nearest relevant border or boundary.
-
B.
locatedNearStateBorderWith
chosen
Indicates that one entity is situated geographically close to the border of a specified state.
-
C.
borderStateNearby
Indicates that one state is geographically close to, but does not necessarily directly touch, the border of another state.
-
D.
nearInternationalBoundary
Indicates that one entity is located close to an international boundary separating two or more countries.
-
E.
countryBorderProximity
Indicates that one country is geographically close to or directly bordering another country.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5278dacc4819089b759744f100e5f |
completed | April 7, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69d5190a6dfc819088262957551808a1 |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:41 p.m.