Triple
T14321720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenwood–Leflore Airport |
E355104
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | Leflore County |
E164489
|
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: Leflore County | Statement: [Greenwood–Leflore Airport, owner, Leflore County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leflore County Context triple: [Greenwood–Leflore Airport, owner, Leflore County]
-
A.
Leflore County
chosen
Leflore County is a county in the Mississippi Delta region of Mississippi, known for its rich blues heritage and agricultural history.
-
B.
Yazoo County
Yazoo County is a largely rural county in west-central Mississippi known for its agricultural economy, Delta landscapes, and county seat of Yazoo City.
-
C.
Lamar County
Lamar County is a county in the state of Georgia, United States, known for its seat in the city of Barnesville and its location in the central part of the state.
-
D.
Lamar County
Lamar County is a rural county in western Alabama known for its small communities and agricultural landscape.
-
E.
Lamar County
Lamar County is a county in northeastern Texas known for its seat in the city of Paris and its location near the Oklahoma border.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de883bf71c8190a9a092a025cf98f0 |
completed | April 14, 2026, 6:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01232149f88190b385fca6a7588d7b |
completed | May 11, 2026, 12:30 a.m. |
Created at: April 10, 2026, 1:13 a.m.