Triple
T2541759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shirley Jones |
E57799
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Ryan Cassidy |
E283792
|
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: Ryan Cassidy | Statement: [Shirley Jones, child, Ryan Cassidy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ryan Cassidy Context triple: [Shirley Jones, child, Ryan Cassidy]
-
A.
Ryan Cassidy
chosen
Ryan Cassidy is an American actor and production designer, and the son of actress Shirley Jones and actor Jack Cassidy.
-
B.
Sean Cahill
Sean Cahill is a relative of former Australian professional soccer player Tim Cahill.
-
C.
Eric Thibault
Eric Thibault is a professional basketball coach best known for leading the WNBA’s Washington Mystics.
-
D.
Ryan Arcidiacono
Ryan Arcidiacono is an American professional basketball player best known for his standout collegiate career as a clutch, championship-winning point guard at Villanova University.
-
E.
Drew Bagnell
Drew Bagnell is a roboticist and machine learning researcher known for his work in autonomous systems and his role as a co-founder and chief scientist at Aurora Innovation.
- 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_69ab4a5212d88190b989ce129f2ad87f |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd2bd92f88190bf100c799f62210c |
completed | March 7, 2026, 7:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af98ab023481908ab51febe79b963c |
completed | March 10, 2026, 4:06 a.m. |
Created at: March 6, 2026, 9:47 p.m.