Triple
T3737036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Aiken |
E79609
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Aiken |
E115528
|
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: Aiken | Statement: [Frank Aiken, familyName, Aiken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aiken Context triple: [Frank Aiken, familyName, Aiken]
-
A.
Aiken
chosen
Aiken is a variant spelling of the surname Aitken, which is of Scottish origin.
-
B.
Cordele
Cordele is a small city in south-central Georgia known as the "Watermelon Capital of the World" and as a regional hub along major highway and rail routes.
-
C.
Aiken, South Carolina
Aiken, South Carolina is a historic city in western South Carolina known for its equestrian culture, winter colony heritage, and tree-lined streets.
-
D.
Macon
Macon is a surname of English and French origin borne by various notable individuals, including American statesman Nathaniel Macon.
-
E.
Macon
Macon is a small town located in Warren County, North Carolina, known for its rural character and proximity to Lake Gaston.
- 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_69ad8b115610819095b02007da5ca3cb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb3d32b081909a993a78b0869db8 |
completed | March 8, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db1e4cc48190bfc1078e9b06d2d9 |
completed | March 14, 2026, 3:50 a.m. |
Created at: March 8, 2026, 3:34 p.m.