Triple
T19807147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elmore County, Alabama |
E475842
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Wetumpka, Alabama |
—
|
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: Wetumpka, Alabama | Statement: [Elmore County, Alabama, contains, Wetumpka, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wetumpka, Alabama Context triple: [Elmore County, Alabama, contains, Wetumpka, Alabama]
-
A.
Wetumpka, Alabama
chosen
Wetumpka, Alabama is a small city in Elmore County known for its historic sites, including nearby Fort Toulouse-Fort Jackson, and its scenic location along the Coosa River.
-
B.
Creola, Alabama
Creola, Alabama is a small city in southwestern Alabama that forms part of the Mobile metropolitan area.
-
C.
Moody, Alabama
Moody, Alabama is a small suburban city in central Alabama that forms part of the Birmingham metropolitan area.
-
D.
Jackson, Alabama
Jackson, Alabama is a small city in Clarke County known historically as a regional center for timber and paper industries in southwestern Alabama.
-
E.
Gadsden, Alabama
Gadsden, Alabama is a small industrial city in northeastern Alabama known historically for its manufacturing plants and labor history.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65428f5c48190be6ae0d6a77675d2 |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:49 p.m.