Triple
T32008187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texline, Texas vicinity |
E817328
|
entity |
| Predicate | nearbyStateLine |
P13917
|
FINISHED |
| Object | Texas–New Mexico state line |
—
|
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: Texas–New Mexico state line | Statement: [Texline, Texas vicinity, nearbyStateLine, Texas–New Mexico state line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyStateLine Context triple: [Texline, Texas vicinity, nearbyStateLine, Texas–New Mexico state line]
-
A.
hasNearbyStateLine
chosen
Indicates that one location is situated close to the boundary line of a neighboring state.
-
B.
nearbyState
Indicates that one state is geographically adjacent to or in close proximity to another state.
-
C.
nearbyStateOrProvince
Indicates that one state or province is geographically close to, but not necessarily directly bordering, another state or province.
-
D.
hasNearbyLine
Indicates that one entity is located close to, or in the vicinity of, a particular line or linear feature.
-
E.
nearByCityState
Indicates that a city is geographically close to or within the same general area as a specified state.
- 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_69f348f9e5d081908cc3f57c4942af52 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd82ed2a4c81908bd7797fbd2e3d08 |
completed | May 8, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fd814cc10481908e4f8123d35a5d0c |
completed | May 8, 2026, 6:23 a.m. |
Created at: May 1, 2026, 12:15 a.m.