Triple
T2512584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Lansing |
E52734
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Clinton County |
E395273
|
NE FINISHED |
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: Clinton County | Statement: [East Lansing, county, Clinton County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clinton County Context triple: [East Lansing, county, Clinton County]
-
A.
Clinton County
chosen
Clinton County is the name of numerous counties in the United States, typically named after prominent American statesmen such as George Clinton or DeWitt Clinton.
-
B.
Greene County
Greene County is a rural county in southwestern Pennsylvania known for its Appalachian landscape, coal mining history, and small-town communities within the greater Pittsburgh region.
-
C.
Greene County
Greene County is a rural county in eastern New York State known for encompassing a significant portion of the scenic Catskill Mountains.
-
D.
Greene County
Greene County is a rural county in western Alabama known for its historical significance in the Black Belt region and its predominantly African American population.
-
E.
Columbia County
Columbia County is a rural county in eastern New York State known for its Hudson River frontage, historic towns, and agricultural landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1efb5c48190a9b47b39a388412b |
completed | March 7, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51c5602f081908dba5df679ca9733 |
completed | March 14, 2026, 8:29 a.m. |
Created at: March 6, 2026, 9:46 p.m.