Triple
T15101331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fuquay Springs |
E360671
|
entity |
| Predicate | hasSuccessor |
P78
|
FINISHED |
| Object | Fuquay-Varina |
E73477
|
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: Fuquay-Varina | Statement: [Fuquay Springs, hasSuccessor, Fuquay-Varina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fuquay-Varina Context triple: [Fuquay Springs, hasSuccessor, Fuquay-Varina]
-
A.
Fuquay-Varina
chosen
Fuquay-Varina is a rapidly growing suburban town in Wake County, North Carolina, known for its historic downtowns and proximity to the Raleigh metropolitan area.
-
B.
Evinayong
Evinayong is a town in mainland Equatorial Guinea that serves as an important local administrative and commercial center.
-
C.
Vanne
Vanne is a river in north-central France that serves as a tributary of the Yonne.
-
D.
Tannay
Tannay is a small lakeside municipality in the canton of Vaud in western Switzerland, situated on the shores of Lake Geneva.
-
E.
Valdosta
Valdosta is a city in southern Georgia known as a regional commercial hub and home to Valdosta State University.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00550007481909e02ee1d597a4d37 |
completed | April 15, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febfdffb6081909012cf0707f5c9f5 |
completed | May 9, 2026, 5:02 a.m. |
Created at: April 10, 2026, 3:04 a.m.