Triple
T7035706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee County, Alabama |
E163376
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Opelika, Alabama |
E132736
|
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: Opelika, Alabama | Statement: [Lee County, Alabama, contains, Opelika, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Opelika, Alabama Context triple: [Lee County, Alabama, contains, Opelika, Alabama]
-
A.
Opelika
chosen
Opelika is a city in eastern Alabama known for its proximity to Auburn and its role as a regional center for industry and commerce.
-
B.
Atmore, Alabama
Atmore, Alabama is a small city in Escambia County near the Florida state line, known historically for its railroad roots and proximity to several state and federal correctional facilities.
-
C.
Cusseta, Alabama
Cusseta, Alabama is a small rural town in eastern Alabama known for its quiet community within Chambers County.
-
D.
Saraland
Saraland is a suburban city in Mobile County, Alabama, known as part of the Mobile metropolitan area and for its residential communities and local industry.
-
E.
Lanett, Alabama
Lanett, Alabama is a small city in eastern Alabama near the Georgia border, historically tied to the textile industry and the Chattahoochee River region.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e220508c8190b8950cf38280b8c2 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8eee797a881909548186742cf7b66 |
completed | March 29, 2026, 9:20 a.m. |
Created at: March 27, 2026, 2:36 p.m.