Triple
T12464100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elgin Baylor |
E297875
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Elgin Gay Baylor |
E297875
|
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: Elgin Gay Baylor | Statement: [Elgin Baylor, fullName, Elgin Gay Baylor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elgin Gay Baylor Context triple: [Elgin Baylor, fullName, Elgin Gay Baylor]
-
A.
Elgin Gay Baylor
chosen
Elgin Gay Baylor was an American professional basketball player and Hall of Famer renowned as one of the NBA’s greatest forwards, primarily starring for the Minneapolis/Los Angeles Lakers in the 1960s.
-
B.
Robert Emmett Bledsoe Baylor
Robert Emmett Bledsoe Baylor was a 19th-century American Baptist judge, politician, and educator best known for co-founding the institution that became Baylor University.
-
C.
Don Baylor
Don Baylor was an American Major League Baseball slugger and later manager, renowned for his power hitting, durability, and leadership on and off the field.
-
D.
Howard Payne
Howard Payne is the ruthless, bomb-obsessed former cop who serves as the primary antagonist in the action film "Speed."
-
E.
Earl Hood
Earl Hood is a motorsport journalist and writer known for his coverage and commentary on racing events and the automotive industry.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94db5efe88190a76949e4ddc3314c |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f1f44f481909c7efdffd2aeac41 |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:56 p.m.