Triple
T9578866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scrubs |
E231117
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Perry Cox
Perry Cox is a sarcastic, tough-love attending physician and mentor on the medical comedy-drama series "Scrubs."
|
E830317
|
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: Perry Cox | Statement: [Scrubs, mainCharacter, Perry Cox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Perry Cox Context triple: [Scrubs, mainCharacter, Perry Cox]
-
A.
Bill DeMott
Bill DeMott is a retired American professional wrestler and wrestling trainer best known for his work in World Championship Wrestling (WCW) and WWE, including a controversial tenure as head trainer for WWE’s developmental system.
-
B.
Will McDonough
Will McDonough is an American sports journalist best known for his long tenure as an NFL reporter and columnist for The Boston Globe and as a pioneering football analyst on national television.
-
C.
Perry Howze
Perry Howze is a screenwriter best known for co-writing the 1988 romantic comedy film "Mystic Pizza."
-
D.
Ward Poulos
Ward Poulos is an entrepreneur best known as a co-founder of the online employment marketplace ZipRecruiter.
-
E.
Donald McEnery
Donald McEnery is an American screenwriter best known for co-writing the Pixar animated film "A Bug's Life."
- 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: Perry Cox Triple: [Scrubs, mainCharacter, Perry Cox]
Generated description
Perry Cox is a sarcastic, tough-love attending physician and mentor on the medical comedy-drama series "Scrubs."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Perry Cox Target entity description: Perry Cox is a sarcastic, tough-love attending physician and mentor on the medical comedy-drama series "Scrubs."
-
A.
Bill DeMott
Bill DeMott is a retired American professional wrestler and wrestling trainer best known for his work in World Championship Wrestling (WCW) and WWE, including a controversial tenure as head trainer for WWE’s developmental system.
-
B.
Will McDonough
Will McDonough is an American sports journalist best known for his long tenure as an NFL reporter and columnist for The Boston Globe and as a pioneering football analyst on national television.
-
C.
Perry Howze
Perry Howze is a screenwriter best known for co-writing the 1988 romantic comedy film "Mystic Pizza."
-
D.
Ward Poulos
Ward Poulos is an entrepreneur best known as a co-founder of the online employment marketplace ZipRecruiter.
-
E.
Donald McEnery
Donald McEnery is an American screenwriter best known for co-writing the Pixar animated film "A Bug's Life."
- 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_69d22840c4548190b1610e2c3cec6220 |
completed | April 5, 2026, 9:15 a.m. |
| NEDg | Description generation | batch_69d229f496c48190bf3bca109b3bc62b |
completed | April 5, 2026, 9:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d22a8494f481909bd6b4936b32679e |
completed | April 5, 2026, 9:25 a.m. |
Created at: March 30, 2026, 8:05 p.m.