Triple
T15481082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sharon, Mississippi |
E376917
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Sharon, Mississippi |
—
|
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: Sharon, Mississippi | Statement: [Sharon, Mississippi, hasName, Sharon, Mississippi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sharon, Mississippi Context triple: [Sharon, Mississippi, hasName, Sharon, Mississippi]
-
A.
Sharon, Mississippi
chosen
Sharon, Mississippi is a small unincorporated community located in Madison County in the central part of the state.
-
B.
Shaw, Mississippi
Shaw, Mississippi is a small rural city in the Mississippi Delta region known for its agricultural surroundings and historically African American community.
-
C.
Shoccoe, Mississippi
Shoccoe, Mississippi is a small unincorporated rural community located in Rankin County in the central part of the state.
-
D.
Sallis, Mississippi
Sallis, Mississippi is a small rural town located in central Mississippi within Attala County.
-
E.
Winona, Mississippi
Winona, Mississippi is a small city in central Mississippi known as a local commercial and transportation hub along Interstate 55.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f8cb4388190a3b4c92c3bb4ad4f |
completed | April 16, 2026, 1:46 a.m. |
Created at: April 10, 2026, 3:34 a.m.