Triple
T5330079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allegheny Front |
E123282
|
entity |
| Predicate | stateBoundaryFor |
P47901
|
FINISHED |
| Object | portions of the Maryland–West Virginia 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: portions of the Maryland–West Virginia border | Statement: [Allegheny Front, stateBoundaryFor, portions of the Maryland–West Virginia border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stateBoundaryFor Context triple: [Allegheny Front, stateBoundaryFor, portions of the Maryland–West Virginia border]
-
A.
isPoliticalBoundary
chosen
Indicates that one entity serves as a dividing line or border that separates distinct political or administrative jurisdictions.
-
B.
borderRegionOf
Indicates that one region lies along, touches, or forms part of the boundary of another region.
-
C.
USStateBorderFor
Indicates that a U.S. state serves as a bordering state for the specified geographic or political entity.
-
D.
provinceBordering
Indicates that two provinces share a common boundary or border with each other.
-
E.
boundaryName
Indicates the designated name or label assigned to a specific boundary or border between entities.
- 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_69bd46477f9081909d242a327d749466 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd859552d8819080758bdd7c43c66a |
completed | March 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69bd84583dbc819088a03e3afb30178c |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2 p.m.