Triple
T22451210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shoresy |
E554993
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Terry Ryan
Terry Ryan is a Canadian former professional ice hockey player who has also worked as an actor and media personality.
|
E1537464
|
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: Terry Ryan | Statement: [Shoresy, hasCastMember, Terry Ryan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terry Ryan Context triple: [Shoresy, hasCastMember, Terry Ryan]
-
A.
Tony DiCicco
Tony DiCicco was an American soccer coach best known for leading the U.S. women’s national team to victory in the 1996 Olympics and the 1999 FIFA Women’s World Cup.
-
B.
Jim Cavanaugh
Jim Cavanaugh is an American businessman and aviation enthusiast best known as the founder of the Cavanaugh Flight Museum, which preserves and displays historic aircraft.
-
C.
Jim Madigan
Jim Madigan is a longtime Northeastern University hockey coach and administrator who became the athletic director overseeing the school's sports programs.
-
D.
Jim Gerald
Jim Gerald was a French actor and comedian known for his roles in early 20th-century cinema and theater.
-
E.
Kevin DiCicco
Kevin DiCicco is a screenwriter best known for creating and writing the family sports film franchise featuring the basketball-playing dog Air Bud.
- 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: Terry Ryan Triple: [Shoresy, hasCastMember, Terry Ryan]
Generated description
Terry Ryan is a Canadian former professional ice hockey player who has also worked as an actor and media personality.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Terry Ryan Target entity description: Terry Ryan is a Canadian former professional ice hockey player who has also worked as an actor and media personality.
-
A.
Tony DiCicco
Tony DiCicco was an American soccer coach best known for leading the U.S. women’s national team to victory in the 1996 Olympics and the 1999 FIFA Women’s World Cup.
-
B.
Jim Cavanaugh
Jim Cavanaugh is an American businessman and aviation enthusiast best known as the founder of the Cavanaugh Flight Museum, which preserves and displays historic aircraft.
-
C.
Jim Madigan
Jim Madigan is a longtime Northeastern University hockey coach and administrator who became the athletic director overseeing the school's sports programs.
-
D.
Jim Gerald
Jim Gerald was a French actor and comedian known for his roles in early 20th-century cinema and theater.
-
E.
Kevin DiCicco
Kevin DiCicco is a screenwriter best known for creating and writing the family sports film franchise featuring the basketball-playing dog Air Bud.
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4ba6a88190a0a79e2c20fa8c08 |
completed | April 29, 2026, 1:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b0c79028c8190bcefe8549a81f777 |
completed | May 18, 2026, 12:56 p.m. |
| NEDg | Description generation | batch_6a0b0d10a50881909fb586a3c529623d |
completed | May 18, 2026, 12:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b0daf9bac819086166985458f6742 |
completed | May 18, 2026, 1:01 p.m. |
Created at: April 16, 2026, 8:48 p.m.