Triple
T15062538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brody |
E379664
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Ken Brody
Ken Brody is a notable individual whose specific public achievements or roles are not clearly identifiable from the given information.
|
E1136377
|
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: Ken Brody | Statement: [Brody, hasNotableBearer, Ken Brody]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ken Brody Context triple: [Brody, hasNotableBearer, Ken Brody]
-
A.
Michael Brody
Michael Brody is a fictional character from the "Jaws" film series, known as the elder son of police chief Martin Brody who later becomes central to the franchise’s shark-related events.
-
B.
Elliot Brody
Elliot Brody is the child of Academy Award–winning American actor Adrien Brody.
-
C.
Phil Bronstein
Phil Bronstein is an American journalist and editor best known for his long tenure at the San Francisco Chronicle and his marriage to actress Sharon Stone.
-
D.
Michael Bauman
Michael Bauman is a cinematographer best known for his work on the film "Licorice Pizza."
-
E.
Johnny Gandelsman
Johnny Gandelsman is a Grammy-winning violinist and producer known for his work with ensembles like Brooklyn Rider and the Silk Road Ensemble, as well as for his innovative solo projects.
- 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: Ken Brody Triple: [Brody, hasNotableBearer, Ken Brody]
Generated description
Ken Brody is a notable individual whose specific public achievements or roles are not clearly identifiable from the given information.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ken Brody Target entity description: Ken Brody is a notable individual whose specific public achievements or roles are not clearly identifiable from the given information.
-
A.
Michael Brody
Michael Brody is a fictional character from the "Jaws" film series, known as the elder son of police chief Martin Brody who later becomes central to the franchise’s shark-related events.
-
B.
Elliot Brody
Elliot Brody is the child of Academy Award–winning American actor Adrien Brody.
-
C.
Phil Bronstein
Phil Bronstein is an American journalist and editor best known for his long tenure at the San Francisco Chronicle and his marriage to actress Sharon Stone.
-
D.
Michael Bauman
Michael Bauman is a cinematographer best known for his work on the film "Licorice Pizza."
-
E.
Johnny Gandelsman
Johnny Gandelsman is a Grammy-winning violinist and producer known for his work with ensembles like Brooklyn Rider and the Silk Road Ensemble, as well as for his innovative solo projects.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedee6a55c8190b40c4672fb46b79b |
completed | April 15, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae0fd7dc8190a10c8eb7542c3088 |
completed | May 9, 2026, 3:46 a.m. |
| NEDg | Description generation | batch_69feafcab944819095317d3058540b8b |
completed | May 9, 2026, 3:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feb038065c8190b60266644db64092 |
completed | May 9, 2026, 3:55 a.m. |
Created at: April 10, 2026, 3:02 a.m.