Triple
T23554419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Island Light |
E578142
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Ashland County |
—
|
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: Ashland County | Statement: [Long Island Light, county, Ashland County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashland County Context triple: [Long Island Light, county, Ashland County]
-
A.
Ashland County
chosen
Ashland County is a largely rural county in north-central Ohio known for its agricultural landscape, small towns, and the city of Ashland as its county seat.
-
B.
Kemper County
Kemper County is a rural county in eastern Mississippi known for its small communities, agricultural landscape, and historical significance in the state.
-
C.
Dixon County
Dixon County is a county-level administrative region in the U.S. state of Nebraska.
-
D.
Morgan County
Morgan County is a rural county in northeastern Colorado known for its agricultural economy and small communities centered around the city of Fort Morgan.
-
E.
Morgan County
Morgan County is a county in northern Alabama known for its seat in Decatur and its role in the Huntsville-Decatur metropolitan area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245fa93448190919cb04534560542 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1aed17fc881908b45dcde14790d42 |
completed | April 29, 2026, 7:10 a.m. |
Created at: April 17, 2026, 6:12 p.m.