Triple
T12967288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norm Sloan |
E321293
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object | Tom Burleson |
E282224
|
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: Tom Burleson | Statement: [Norm Sloan, notableStudent, Tom Burleson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Burleson Context triple: [Norm Sloan, notableStudent, Tom Burleson]
-
A.
Tom Burleson
chosen
Tom Burleson is a retired American professional basketball center best known for his shot-blocking and rebounding in the NBA during the 1970s.
-
B.
Grant Bardsley
Grant Bardsley is a British voice actor best known for voicing the protagonist Taran in Disney’s animated film "The Black Cauldron."
-
C.
Don Dodson
Don Dodson is an individual whose name is associated with or referenced by the term "Dodson."
-
D.
Dan Tucker
Dan Tucker is the titular, comical protagonist of the 19th-century American minstrel song "Old Dan Tucker," often depicted as a boisterous, rustic figure.
-
E.
Tom Brumley
Tom Brumley was an influential American pedal steel guitarist best known for his work with Buck Owens and the Buckaroos, helping define the Bakersfield sound in country music.
- 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e3f702481908f0f90f4f12d3f4d |
completed | April 10, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eacea664819096940ba4d409d264 |
completed | May 3, 2026, 6:27 a.m. |
Created at: April 9, 2026, 8:30 p.m.