Triple
T26548487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monroe County, Virginia |
E671606
|
entity |
| Predicate | territoryLaterIncludedIn |
P59198
|
FINISHED |
| Object | Monroe County, West Virginia |
—
|
NE NERFINISHED |
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: Monroe County, West Virginia | Statement: [Monroe County, Virginia, territoryLaterIncludedIn, Monroe County, West Virginia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: territoryLaterIncludedIn Context triple: [Monroe County, Virginia, territoryLaterIncludedIn, Monroe County, West Virginia]
-
A.
territoryOriginallyIncluded
Indicates that an earlier or original territorial boundary encompassed the referenced area or entity.
-
B.
territoryIncluded
Indicates that one territory is geographically or administratively contained within another territory.
-
C.
laterTerritory
chosen
Indicates that one territory is a subsequent or successor territory to another in time.
-
D.
sometimesIncludesTerritory
Indicates that one entity occasionally, but not consistently, encompasses or contains the territory of another entity.
-
E.
territoryCorrespondedTo
Indicates that one territory matched, aligned with, or was equivalent to another territory in scope, boundaries, or designation.
- 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_69eeb32163f08190af5f81282738e27a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f650c70d7c819093d9a0f005f7c8d5 |
completed | May 2, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 1:45 a.m.