Triple
T2567180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brewster Kahle |
E57378
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Kahle |
E57378
|
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: Kahle | Statement: [Brewster Kahle, hasSurname, Kahle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kahle Context triple: [Brewster Kahle, hasSurname, Kahle]
-
A.
Kahle
chosen
Kahle is a surname most notably associated with Brewster Kahle, the American computer engineer and digital librarian who founded the Internet Archive.
-
B.
Finklea
Finklea is the birth surname of American actress and dancer Cyd Charisse, known for her roles in classic Hollywood musicals.
-
C.
Karns
Karns is an unincorporated suburban community in Knox County, Tennessee, situated within the Knoxville metropolitan area.
-
D.
Wylie
Wylie is a suburban city in the Dallas–Fort Worth metropolitan area in northeastern Texas.
-
E.
Kuppenheimer
Kuppenheimer was a prominent American men's clothing company best known for its high-quality suits and influential early 20th-century advertising campaigns.
- 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3602ed08190aad0f9c7ac577eb0 |
completed | March 7, 2026, 7:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af6565e05081909dc12aa3240de5f2 |
completed | March 10, 2026, 12:27 a.m. |
Created at: March 6, 2026, 9:48 p.m.