Triple
T15275903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glen Falls |
E365139
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Erie 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: Erie County | Statement: [Glen Falls, county, Erie County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erie County Context triple: [Glen Falls, county, Erie County]
-
A.
Erie County, New York
Erie County, New York is a populous county in western New York State that includes the city of Buffalo and several large suburbs.
-
B.
Erie County, Ohio
Erie County, Ohio is a county in northern Ohio along the shores of Lake Erie, known for including the city of Sandusky and attractions such as Cedar Point amusement park.
-
C.
Monroe County
Monroe County is a rural county in southern West Virginia known for its scenic Appalachian landscapes, agriculture, and historic small towns.
-
D.
Monroe County
Monroe County is a county in the U.S. state of Michigan located along the western shore of Lake Erie, south of Detroit.
-
E.
Monroe County
Monroe County is a rural county in south-central Iowa known for its agricultural landscape and small communities such as Melrose.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00952731c8190bf6a5e6e10c95b94 |
completed | April 15, 2026, 9:55 p.m. |
Created at: April 10, 2026, 3:14 a.m.