Triple
T12476182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cypselus |
E298181
|
entity |
| Predicate | country |
P26
|
FINISHED |
| Object | Corinth |
E61494
|
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: Corinth | Statement: [Cypselus, country, Corinth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Corinth Context triple: [Cypselus, country, Corinth]
-
A.
Corinth
Corinth is a small unincorporated community located in Coweta County, Georgia, United States.
-
B.
Corinth
chosen
Corinth was an influential ancient Greek city-state strategically located on the Isthmus of Corinth, known for its wealth, maritime trade, and cultural significance.
-
C.
Corinth
Corinth is a small town and village in Saratoga County, New York, known for its historic paper mills and location along the Hudson River near the Adirondack foothills.
-
D.
Corinth
Corinth is a suburban city within the Dallas–Fort Worth metropolitan area in Texas, known for its residential communities and proximity to major urban centers.
-
E.
Corinto
Corinto is a municipality located in the Morazán Department of northeastern El Salvador, known for its rural character and mountainous landscapes.
- 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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dcb194c81908b5e0320ddfd463c |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f25462881908dccb831b474875d |
completed | May 2, 2026, 6:15 p.m. |
Created at: April 8, 2026, 9:56 p.m.