Triple
T8766591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Logan Lucky |
E208352
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object | West Virginia |
E24143
|
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: West Virginia | Statement: [Logan Lucky, setting, West Virginia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: West Virginia Context triple: [Logan Lucky, setting, West Virginia]
-
A.
West Virginia
chosen
West Virginia is a landlocked, mountainous U.S. state in the Appalachian region, known for its coal mining history, outdoor recreation, and distinct cultural heritage.
-
B.
WV
WV is the postcode area covering Wolverhampton and surrounding parts of the West Midlands in England.
-
C.
Virginia
Virginia is a small community located within the town of Georgina in Ontario, Canada.
-
D.
Virginia
Virginia is a U.S. state in the Mid-Atlantic and Southeastern regions, known for its pivotal role in American history, including being home to several early presidents and key Revolutionary and Civil War sites.
-
E.
Kentucky
Kentucky is a southeastern U.S. state known for its horse racing, bourbon distilleries, bluegrass music, and diverse landscapes ranging from Appalachian mountains to fertile river valleys.
- 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_69ca835df7e08190ac875664cca8f9ca |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5ee97fd0819087ef8fe14b37ae43 |
completed | March 31, 2026, 11:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf519f029081908ad0ae79f35b3e9d |
completed | April 3, 2026, 5:35 a.m. |
Created at: March 30, 2026, 6:41 p.m.