Triple
T5749629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crisp County |
E126817
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Cordele |
E141398
|
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: Cordele | Statement: [Crisp County, hasSettlement, Cordele]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cordele Context triple: [Crisp County, hasSettlement, Cordele]
-
A.
Cordele
chosen
Cordele is a small city in south-central Georgia known as the "Watermelon Capital of the World" and as a regional hub along major highway and rail routes.
-
B.
Aiken
Aiken is a variant spelling of the surname Aitken, which is of Scottish origin.
-
C.
Aiken, South Carolina
Aiken, South Carolina is a historic city in western South Carolina known for its equestrian culture, winter colony heritage, and tree-lined streets.
-
D.
Titisee-Neustadt
Titisee-Neustadt is a popular resort town in Germany’s Black Forest region, known for its scenic lake Titisee, winter sports facilities, and tourism.
-
E.
Onslow
Onslow is a remote coastal town in Western Australia’s Pilbara region, known for its role in the local resources industry and as a gateway to nearby marine and outback attractions.
- 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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0288870fc819080e883c9d589359b |
completed | March 22, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a167f2508190a8dd507f237e771b |
completed | March 23, 2026, 2:11 a.m. |
Created at: March 22, 2026, 3:48 p.m.