Triple
T15620020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessamine County |
E375525
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Wilmore |
E857248
|
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: Wilmore | Statement: [Jessamine County, containsSettlement, Wilmore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wilmore Context triple: [Jessamine County, containsSettlement, Wilmore]
-
A.
Wilmore
Wilmore is an English-language surname borne by various notable individuals across fields such as entertainment, sports, and public service.
-
B.
Wilmore
chosen
Wilmore is a small city in central Kentucky known for its strong Christian academic community and as the home of Asbury University and Asbury Theological Seminary.
-
C.
Mauldin
Mauldin is a city in South Carolina, United States, known as a suburban community within the Greenville metropolitan area.
-
D.
Mauldin
Mauldin is the surname of American music producer, songwriter, and record executive Jermaine Dupri.
-
E.
Temperanceville
Temperanceville is a small community within the Township of King in Ontario, Canada, known for its rural character and historic roots.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e997ce481909b2f10d25705fbc6 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f3b643c819093230df6cfe440b9 |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 10, 2026, 4:13 a.m.