Triple
T10101063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Jordan |
E216199
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Juanita Vanoy |
E216199
|
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: Juanita Vanoy | Statement: [Michael Jordan, spouse, Juanita Vanoy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Juanita Vanoy Context triple: [Michael Jordan, spouse, Juanita Vanoy]
-
A.
Juanita Vanoy
chosen
Juanita Vanoy is a former model and Chicago-based real estate professional best known as the ex-wife of basketball legend Michael Jordan.
-
B.
Jeanne Weaver
Jeanne Weaver is a member of the 2nd Massachusetts Militia Regiment, a state military unit associated with Massachusetts.
-
C.
Maria Mauban
Maria Mauban was a French actress known for her roles in European cinema of the 1940s and 1950s, including notable performances in Italian neorealist and French films.
-
D.
Therese Larimore
Therese Larimore is a character appearing in the horror anthology film "Trilogy of Terror."
-
E.
Diana Rathbun
Diana Rathbun is a film producer best known for her work on the epic historical war movie "Troy."
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd09878f88190bcfa2c81fb10e821 |
completed | April 2, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f489b62b808190a3fc89e73e8ae2f7 |
completed | May 1, 2026, 11:08 a.m. |
Created at: March 30, 2026, 9:02 p.m.