Triple
T10396603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tin Star |
E245036
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Ryan Kennedy
Ryan Kennedy is a Canadian actor known for his roles in television series such as the crime drama "Tin Star."
|
E863699
|
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 Kennedy | Statement: [Tin Star, starring, Ryan Kennedy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ryan Kennedy Context triple: [Tin Star, starring, Ryan Kennedy]
-
A.
Sam Kennedy
Sam Kennedy is a Major League Baseball executive best known for serving as the president and CEO of the Boston Red Sox.
-
B.
Sean Kennedy
Sean Kennedy is the central protagonist of the film "Hustle," around whom the story’s primary conflicts and character development revolve.
-
C.
Dom Kennedy
Dom Kennedy is a Los Angeles-based hip-hop artist known for his laid-back West Coast sound and independent releases that have cultivated a strong underground following.
-
D.
Kevin Kennedy
Kevin Kennedy is a screenwriter known for co-writing the 2004 drama film "The Assassination of Richard Nixon."
-
E.
Christopher G. Kennedy
Christopher G. Kennedy is an American businessman and member of the Kennedy political family, known for his work in real estate and public service in Illinois.
- 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 Kennedy Triple: [Tin Star, starring, Ryan Kennedy]
Generated description
Ryan Kennedy is a Canadian actor known for his roles in television series such as the crime drama "Tin Star."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ryan Kennedy Target entity description: Ryan Kennedy is a Canadian actor known for his roles in television series such as the crime drama "Tin Star."
-
A.
Sam Kennedy
Sam Kennedy is a Major League Baseball executive best known for serving as the president and CEO of the Boston Red Sox.
-
B.
Sean Kennedy
Sean Kennedy is the central protagonist of the film "Hustle," around whom the story’s primary conflicts and character development revolve.
-
C.
Dom Kennedy
Dom Kennedy is a Los Angeles-based hip-hop artist known for his laid-back West Coast sound and independent releases that have cultivated a strong underground following.
-
D.
Kevin Kennedy
Kevin Kennedy is a screenwriter known for co-writing the 2004 drama film "The Assassination of Richard Nixon."
-
E.
Christopher G. Kennedy
Christopher G. Kennedy is an American businessman and member of the Kennedy political family, known for his work in real estate and public service in Illinois.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9cf79348190975d6c1791e3b621 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e7adc3881909731d5289f370b8b |
completed | April 10, 2026, 4:37 a.m. |
| NEDg | Description generation | batch_69d889c45b588190ad103b4bc8cc5fbd |
completed | April 10, 2026, 5:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d88dbbe97c8190861e08f3ff39f91b |
completed | April 10, 2026, 5:42 a.m. |
Created at: April 6, 2026, 12:06 p.m.