Triple
T33255768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huntington–Ashland metropolitan area |
E851373
|
entity |
| Predicate | crossesStateBorders |
P185341
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Huntington–Ashland metropolitan area, crossesStateBorders, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossesStateBorders Context triple: [Huntington–Ashland metropolitan area, crossesStateBorders, true]
-
A.
crossesJurisdictions
Indicates that an action, process, or entity extends beyond a single legal or administrative authority and involves multiple jurisdictions.
-
B.
crossesInternationalBoundaryAt
Indicates that one entity passes from one country’s territory into another at a specific boundary location.
-
C.
crossesBorderOf
Indicates that one entity passes from one side of the boundary of another entity (typically a region or area) to the other side, traversing its border.
-
D.
locatedNearStateBorderWith
Indicates that one entity is situated geographically close to the border of a specified state.
-
E.
crossesRegion
Indicates that an entity moves through or passes across the spatial extent of a specified region.
- F. None of above. chosen
Provenance (4 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_69f34963135c819084e7f1d483421f00 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be520f148190ba200bf3dbf40656 |
completed | May 3, 2026, 9:29 p.m. |
Created at: May 1, 2026, 1:31 a.m.