Triple
T2479758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shirley Jones |
E55184
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Ryan Cassidy
Ryan Cassidy is an American actor and production designer, and the son of actress Shirley Jones and actor Jack Cassidy.
|
E283792
|
NE FINISHED |
How this triple was built (4 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, hasChild, Ryan Cassidy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ryan Cassidy Context triple: [Shirley Jones, hasChild, Ryan Cassidy]
-
A.
Sean Cahill
Sean Cahill is a relative of former Australian professional soccer player Tim Cahill.
-
B.
Eric Thibault
Eric Thibault is a professional basketball coach best known for leading the WNBA’s Washington Mystics.
-
C.
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.
-
D.
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.
-
E.
Dan Bouchard
Dan Bouchard is a former Canadian professional ice hockey goaltender best known for his NHL career with teams such as the Atlanta Flames and Quebec Nordiques.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ryan Cassidy Triple: [Shirley Jones, hasChild, Ryan Cassidy]
Generated description
Ryan Cassidy is an American actor and production designer, and the son of actress Shirley Jones and actor Jack Cassidy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ryan Cassidy Target entity description: Ryan Cassidy is an American actor and production designer, and the son of actress Shirley Jones and actor Jack Cassidy.
-
A.
Sean Cahill
Sean Cahill is a relative of former Australian professional soccer player Tim Cahill.
-
B.
Eric Thibault
Eric Thibault is a professional basketball coach best known for leading the WNBA’s Washington Mystics.
-
C.
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.
-
D.
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.
-
E.
Dan Bouchard
Dan Bouchard is a former Canadian professional ice hockey goaltender best known for his NHL career with teams such as the Atlanta Flames and Quebec Nordiques.
- F. None of above. chosen
Provenance (5 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_69ab49e279e88190ab10d7248aea9d11 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd160a9708190b28d2f5538ea129a |
completed | March 7, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af906499688190a21984590b8caadc |
completed | March 10, 2026, 3:30 a.m. |
| NEDg | Description generation | batch_69af90f63dac8190b3282b5029d22fab |
completed | March 10, 2026, 3:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af918e7b50819082f37f9cdb3271a2 |
completed | March 10, 2026, 3:35 a.m. |
Created at: March 6, 2026, 9:45 p.m.