Triple
T13625447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Tecumseh Sherman |
E325567
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Lancaster, Ohio |
—
|
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: Lancaster, Ohio | Statement: [William Tecumseh Sherman, birthPlace, Lancaster, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lancaster, Ohio Context triple: [William Tecumseh Sherman, birthPlace, Lancaster, Ohio]
-
A.
Lancaster, Ohio
chosen
Lancaster, Ohio is a small city in central Ohio known for its historic downtown, glassmaking heritage, and proximity to the Hocking Hills region.
-
B.
New London, Ohio
New London, Ohio is a small village in Huron County known for its rural character and location in north-central Ohio.
-
C.
Wilmington, Ohio
Wilmington, Ohio is a small city in southwestern Ohio known historically as a regional transportation hub and home to a major air park and agricultural community.
-
D.
Harrisburg, Ohio
Harrisburg, Ohio is a small village in central Ohio that functions as part of the Columbus metropolitan area.
-
E.
Whitehouse, Ohio
Whitehouse, Ohio is a small village in northwest Ohio known for its suburban-rural character and proximity to the city of Toledo.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbe9c72c88190be3d7a3f2e96afbc |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:50 p.m.