Triple
T19788228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sadie Liza Vaughan |
E475333
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Rudy Law |
—
|
NE NERFINISHED |
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: Rudy Law | Statement: [Sadie Liza Vaughan, child, Rudy Law]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rudy Law Context triple: [Sadie Liza Vaughan, child, Rudy Law]
-
A.
Rudy Law
chosen
Rudy Law is one of the children of English actor Jude Law, known primarily for his connection to the prominent film star.
-
B.
Rudy Bond
Rudy Bond was an American character actor known for his supporting roles in mid-20th-century films and stage productions.
-
C.
Durand "Rudy" Macklin
Durand "Rudy" Macklin is a former American college basketball star best known as one of Louisiana State University's all-time great players and leading rebounders.
-
D.
Dennis Scott
Dennis Scott is a former American professional basketball player best known as a prolific three-point shooter in the NBA, particularly with the Orlando Magic in the 1990s.
-
E.
Lawrence Riley
Lawrence Riley was an American playwright and screenwriter best known for his work on mid-20th-century stage and film comedies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65389c9ac81909e61b3cbb9213e72 |
completed | April 20, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:49 p.m.