Triple
T3109610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clio, Alabama |
E64917
|
entity |
| Predicate | hasNotablePerson |
P304
|
FINISHED |
| Object | Lurleen Wallace |
E60990
|
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: Lurleen Wallace | Statement: [Clio, Alabama, hasNotablePerson, Lurleen Wallace]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lurleen Wallace Context triple: [Clio, Alabama, hasNotablePerson, Lurleen Wallace]
-
A.
Lurleen Wallace
chosen
Lurleen Wallace was an American politician who became the first female governor of Alabama, serving from 1967 until her death.
-
B.
Norma Talmadge
Norma Talmadge was a prominent American silent film actress and producer, renowned in the 1910s and 1920s for her dramatic roles and status as one of Hollywood’s biggest stars.
-
C.
Susan Moore, Alabama
Susan Moore, Alabama is a small rural town in Blount County known for its close-knit community and agricultural surroundings.
-
D.
Betty Talmadge
Betty Talmadge was an American political spouse, cookbook author, and influential figure in Georgia’s social and political circles during the mid-20th century.
-
E.
Kathy Evers
Kathy Evers is the First Lady of Wisconsin and the wife of Governor Tony Evers.
- 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada2a0ab2481908db50738ec3ad0fb |
completed | March 8, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b203902a6881909b20589fad629640 |
completed | March 12, 2026, 12:06 a.m. |
Created at: March 8, 2026, 3:04 p.m.