Triple
T23654175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McGaheysville, Virginia |
E584247
|
entity |
| Predicate | locatedInCountySeatMetroArea |
P80214
|
FINISHED |
| Object | Harrisonburg metropolitan area |
—
|
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: Harrisonburg metropolitan area | Statement: [McGaheysville, Virginia, locatedInCountySeatMetroArea, Harrisonburg metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInCountySeatMetroArea Context triple: [McGaheysville, Virginia, locatedInCountySeatMetroArea, Harrisonburg metropolitan area]
-
A.
locatedInCountySeatOfCounty
Indicates that one entity is located in the county seat city or town of the specified county.
-
B.
isInCountySeatMetroArea
chosen
Indicates that an entity is located within the metropolitan area of a county seat.
-
C.
isInCountySeatOf
Indicates that one entity is located within the town or city that serves as the administrative center (county seat) of a specified county.
-
D.
locatedNearMetropolitanArea
Indicates that one entity is situated in close geographic proximity to a metropolitan (urban) area.
-
E.
isInCountySeatAreaOfInfluence
Indicates that one location lies within the geographic or functional area of influence of a county seat.
- 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_69e248ffc0888190ae23c4731eb8b7ac |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b35a513c8190a251fe2f55b23d7c |
completed | April 29, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:49 p.m.