Triple
T11405161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patrick Cassidy |
E270216
|
entity |
| Predicate | sibling |
P363
|
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: [Patrick Cassidy, sibling, Ryan Cassidy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ryan Cassidy Context triple: [Patrick Cassidy, sibling, 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.
Ryan Sissons
Ryan Sissons is a New Zealand triathlete who has represented his country at multiple international competitions, including the Olympic Games and World Triathlon Series events.
-
D.
Nick Cassidy
Nick Cassidy is the central protagonist of the thriller film "Man on a Ledge," a former cop who stages a dramatic high-rise standoff to prove his innocence in a major heist.
-
E.
Preston D'Ambrosio
Preston D'Ambrosio is a fictional character appearing in the film "In Too Deep."
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8014c820c81908538ba4a08e13230 |
completed | April 9, 2026, 7:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e8cc338081908da977b5b7c6bef3 |
completed | April 20, 2026, 8:50 a.m. |
Created at: April 8, 2026, 9:34 p.m.