Triple
T2516231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Breaking Bad |
E55418
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Saul Goodman
Saul Goodman is a flamboyant, morally flexible criminal lawyer known for his shady legal tactics and comic relief in the Breaking Bad universe.
|
E275834
|
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: Saul Goodman | Statement: [Breaking Bad, mainCharacter, Saul Goodman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saul Goodman Context triple: [Breaking Bad, mainCharacter, Saul Goodman]
-
A.
Walter Black
Walter Black is the troubled, depressed protagonist of the film "The Beaver," who begins communicating through a beaver hand puppet as a coping mechanism.
-
B.
Gob Bluth
Gob Bluth is a vain, inept magician and the frequently self-sabotaging eldest son of the Bluth family in the television sitcom "Arrested Development."
-
C.
Craig Michael Brockman
Craig Michael Brockman is a songwriter best known for co-writing Christina Aguilera’s hit single "Dirrty."
-
D.
Max Cady
Max Cady is a sadistic ex-convict who obsessively stalks and terrorizes the family of the lawyer he blames for his imprisonment in the thriller film "Cape Fear."
-
E.
Sid Silvers
Sid Silvers was an American comedian, actor, and writer known for his work in early Hollywood musicals and comedies.
- 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: Saul Goodman Triple: [Breaking Bad, mainCharacter, Saul Goodman]
Generated description
Saul Goodman is a flamboyant, morally flexible criminal lawyer known for his shady legal tactics and comic relief in the Breaking Bad universe.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saul Goodman Target entity description: Saul Goodman is a flamboyant, morally flexible criminal lawyer known for his shady legal tactics and comic relief in the Breaking Bad universe.
-
A.
Walter Black
Walter Black is the troubled, depressed protagonist of the film "The Beaver," who begins communicating through a beaver hand puppet as a coping mechanism.
-
B.
Gob Bluth
Gob Bluth is a vain, inept magician and the frequently self-sabotaging eldest son of the Bluth family in the television sitcom "Arrested Development."
-
C.
Craig Michael Brockman
Craig Michael Brockman is a songwriter best known for co-writing Christina Aguilera’s hit single "Dirrty."
-
D.
Max Cady
Max Cady is a sadistic ex-convict who obsessively stalks and terrorizes the family of the lawyer he blames for his imprisonment in the thriller film "Cape Fear."
-
E.
Sid Silvers
Sid Silvers was an American comedian, actor, and writer known for his work in early Hollywood musicals and comedies.
- 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd20f8d0c8190bfdcb99a12f59d59 |
completed | March 7, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2b9aa5cc81908c2e09ce18f2e98e |
completed | March 9, 2026, 8:20 p.m. |
| NEDg | Description generation | batch_69af508c28f48190afc4aa1bc3c9adf3 |
completed | March 9, 2026, 10:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69af5155f85081908dd4a1859d0f7907 |
completed | March 9, 2026, 11:01 p.m. |
Created at: March 6, 2026, 9:46 p.m.