Triple
T12138941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cobb |
E289132
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Scott Burkholder
Scott Burkholder is an actor known for his role in the television series "Cobb."
|
E969651
|
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: Scott Burkholder | Statement: [Cobb, castMember, Scott Burkholder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scott Burkholder Context triple: [Cobb, castMember, Scott Burkholder]
-
A.
Craig R. Baxley
Craig R. Baxley is an American film and television director and former stunt coordinator known for his work on high-octane action projects in the 1980s and 1990s.
-
B.
Jeremy Bulloch
Jeremy Bulloch was an English actor best known for originating the role of Boba Fett in the original Star Wars trilogy.
-
C.
Perry Cox
Perry Cox is a sarcastic, tough-love attending physician and mentor on the medical comedy-drama series "Scrubs."
-
D.
James T. Broyhill
James T. Broyhill was a long-serving Republican U.S. Congressman from North Carolina who later briefly served in the U.S. Senate.
-
E.
Jeffrey B. Skiles
Jeffrey B. Skiles is an American airline pilot best known as the first officer who helped successfully ditch US Airways Flight 1549 on the Hudson River in 2009.
- 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: Scott Burkholder Triple: [Cobb, castMember, Scott Burkholder]
Generated description
Scott Burkholder is an actor known for his role in the television series "Cobb."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Scott Burkholder Target entity description: Scott Burkholder is an actor known for his role in the television series "Cobb."
-
A.
Craig R. Baxley
Craig R. Baxley is an American film and television director and former stunt coordinator known for his work on high-octane action projects in the 1980s and 1990s.
-
B.
Jeremy Bulloch
Jeremy Bulloch was an English actor best known for originating the role of Boba Fett in the original Star Wars trilogy.
-
C.
Perry Cox
Perry Cox is a sarcastic, tough-love attending physician and mentor on the medical comedy-drama series "Scrubs."
-
D.
James T. Broyhill
James T. Broyhill was a long-serving Republican U.S. Congressman from North Carolina who later briefly served in the U.S. Senate.
-
E.
Jeffrey B. Skiles
Jeffrey B. Skiles is an American airline pilot best known as the first officer who helped successfully ditch US Airways Flight 1549 on the Hudson River in 2009.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9158eef48819083bdce283a363414 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a7baee88190a32a5a3cd0b8a326 |
completed | May 2, 2026, 2:30 p.m. |
| NEDg | Description generation | batch_69f60bdb39f48190ad6bc51db6c34163 |
completed | May 2, 2026, 2:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60d4c30448190874f253b864ef61e |
completed | May 2, 2026, 2:42 p.m. |
Created at: April 8, 2026, 9:49 p.m.