Triple
T2458700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mad Men |
E54481
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Pete Campbell
Pete Campbell is an ambitious and often morally conflicted advertising account executive in the television drama series "Mad Men."
|
E268674
|
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: Pete Campbell | Statement: [Mad Men, mainCharacter, Pete Campbell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pete Campbell Context triple: [Mad Men, mainCharacter, Pete Campbell]
-
A.
Peter Spears
Peter Spears is an American film producer and actor best known for his work on acclaimed independent films such as "Nomadland" and "Call Me by Your Name."
-
B.
Jack O'Callahan
Jack O'Callahan is an American former defenseman best known for being part of the "Miracle on Ice" U.S. team that won gold at the 1980 Winter Olympics before going on to play in the NHL.
-
C.
Pete
Pete is the nickname of Grover Cleveland Alexander, a Hall of Fame Major League Baseball pitcher and one of the greatest hurlers of the early 20th century.
-
D.
Pete
Pete is a common masculine given name, typically used as a familiar or informal form of the name Peter.
-
E.
Pete
Pete is a classic Disney cartoon villain, best known as Mickey Mouse’s burly, antagonistic foe in the Mickey Mouse franchise.
- 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: Pete Campbell Triple: [Mad Men, mainCharacter, Pete Campbell]
Generated description
Pete Campbell is an ambitious and often morally conflicted advertising account executive in the television drama series "Mad Men."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pete Campbell Target entity description: Pete Campbell is an ambitious and often morally conflicted advertising account executive in the television drama series "Mad Men."
-
A.
Peter Spears
Peter Spears is an American film producer and actor best known for his work on acclaimed independent films such as "Nomadland" and "Call Me by Your Name."
-
B.
Jack O'Callahan
Jack O'Callahan is an American former defenseman best known for being part of the "Miracle on Ice" U.S. team that won gold at the 1980 Winter Olympics before going on to play in the NHL.
-
C.
Pete
Pete is the nickname of Grover Cleveland Alexander, a Hall of Fame Major League Baseball pitcher and one of the greatest hurlers of the early 20th century.
-
D.
Pete
Pete is a common masculine given name, typically used as a familiar or informal form of the name Peter.
-
E.
Pete
Pete is a classic Disney cartoon villain, best known as Mickey Mouse’s burly, antagonistic foe in the Mickey Mouse franchise.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd10a35f88190b102a2cb5c88146e |
completed | March 7, 2026, 7:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef0cd7adc8190b855eb28285fefc5 |
completed | March 9, 2026, 4:09 p.m. |
| NEDg | Description generation | batch_69aef537e0588190b6838ef34d1031ab |
completed | March 9, 2026, 4:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69aef98dcbd08190a371019f616ad820 |
completed | March 9, 2026, 4:47 p.m. |
Created at: March 6, 2026, 9:44 p.m.