Triple
T9578868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scrubs |
E231117
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Bob Kelso
Bob Kelso is a fictional, often sarcastic and bureaucratic chief of medicine on the television series "Scrubs."
|
E828190
|
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: Bob Kelso | Statement: [Scrubs, mainCharacter, Bob Kelso]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bob Kelso Context triple: [Scrubs, mainCharacter, Bob Kelso]
-
A.
Don Dodson
Don Dodson is an individual whose name is associated with or referenced by the term "Dodson."
-
B.
Karl Pitterson
Karl Pitterson is a Jamaican record producer and audio engineer best known for his work on classic reggae and dub recordings in the 1970s and 1980s.
-
C.
Thomas Kinnear
Thomas Kinnear is a fictional Canadian gentleman and murder victim in Margaret Atwood’s novel "Alias Grace," whose death is central to the story’s mystery.
-
D.
Ted Cheesman
Ted Cheesman was a film editor best known for his work on classic Hollywood productions, including the 1933 monster film "King Kong."
-
E.
Cliff Clark
Cliff Clark was an American character actor active in the 1930s and 1940s, often appearing in supporting roles in Hollywood films.
- 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: Bob Kelso Triple: [Scrubs, mainCharacter, Bob Kelso]
Generated description
Bob Kelso is a fictional, often sarcastic and bureaucratic chief of medicine on the television series "Scrubs."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bob Kelso Target entity description: Bob Kelso is a fictional, often sarcastic and bureaucratic chief of medicine on the television series "Scrubs."
-
A.
Don Dodson
Don Dodson is an individual whose name is associated with or referenced by the term "Dodson."
-
B.
Karl Pitterson
Karl Pitterson is a Jamaican record producer and audio engineer best known for his work on classic reggae and dub recordings in the 1970s and 1980s.
-
C.
Thomas Kinnear
Thomas Kinnear is a fictional Canadian gentleman and murder victim in Margaret Atwood’s novel "Alias Grace," whose death is central to the story’s mystery.
-
D.
Ted Cheesman
Ted Cheesman was a film editor best known for his work on classic Hollywood productions, including the 1933 monster film "King Kong."
-
E.
Cliff Clark
Cliff Clark was an American character actor active in the 1930s and 1940s, often appearing in supporting roles in Hollywood films.
- 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_69ca848091c48190bc313d6620d09555 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99aece1081908287e03106de020f |
completed | April 1, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eab0860c819091b0169f82eac47f |
completed | April 5, 2026, 4:53 a.m. |
| NEDg | Description generation | batch_69d1edda5b748190a0d7a1449cad2f68 |
completed | April 5, 2026, 5:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1ee6545208190baedf170f129ae84 |
completed | April 5, 2026, 5:08 a.m. |
Created at: March 30, 2026, 8:05 p.m.