Triple
T11315708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheryl Swoopes |
E267959
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Swoopes |
E267959
|
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: Swoopes | Statement: [Sheryl Swoopes, familyName, Swoopes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Swoopes Context triple: [Sheryl Swoopes, familyName, Swoopes]
-
A.
Sheryl Swoopes
chosen
Sheryl Swoopes is a pioneering American basketball player widely regarded as one of the greatest in women’s basketball history, known for her collegiate stardom, WNBA success, and multiple Olympic gold medals.
-
B.
Sharia Bryant
Sharia Bryant is one of the daughters of former NBA star Kobe Bryant’s parents, making her Kobe Bryant’s sister.
-
C.
Tina Thompson
Tina Thompson is a Hall of Fame American basketball player and four-time WNBA champion, widely regarded as one of the league’s greatest forwards.
-
D.
Teresa Weatherspoon
Teresa Weatherspoon is a Hall of Fame American basketball player and coach best known as an original WNBA star and defensive standout at point guard.
-
E.
Kelly Tisdale
Kelly Tisdale is an American café owner and former restaurateur best known as the wife of comedian and actor Mike Myers.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c2c7b081909af8acebc8aa93aa |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a9e66588190b71e0f60133a8995 |
completed | April 19, 2026, 5:02 p.m. |
Created at: April 8, 2026, 9:32 p.m.