Triple
T17618316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunhill Records |
E429642
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Jay Lasker
Jay Lasker was an American music industry executive best known for leading major record labels and shaping the careers of numerous popular artists in the mid-20th century.
|
E1278007
|
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: Jay Lasker | Statement: [Dunhill Records, foundedBy, Jay Lasker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jay Lasker Context triple: [Dunhill Records, foundedBy, Jay Lasker]
-
A.
Lawrence Lasker
Lawrence Lasker is an American film producer and screenwriter best known for his work on acclaimed dramas and science-themed films such as "Awakenings" and "WarGames."
-
B.
Lewis L. Lasker
Lewis L. Lasker was a notable figure significant enough in his community or field to have the Lasker Rink named in his honor.
-
C.
Mike Lasker
Mike Lasker is a visual effects supervisor and cinematographer known for his work on the animated film "The Mitchells vs. the Machines."
-
D.
Alex Lasker
Alex Lasker is a screenwriter best known for co-writing the military action film "Tears of the Sun."
-
E.
Reuben Lasker
Reuben Lasker was a prominent American fisheries biologist known for his influential research on fish larvae and marine ecosystems.
- 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: Jay Lasker Triple: [Dunhill Records, foundedBy, Jay Lasker]
Generated description
Jay Lasker was an American music industry executive best known for leading major record labels and shaping the careers of numerous popular artists in the mid-20th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jay Lasker Target entity description: Jay Lasker was an American music industry executive best known for leading major record labels and shaping the careers of numerous popular artists in the mid-20th century.
-
A.
Lawrence Lasker
Lawrence Lasker is an American film producer and screenwriter best known for his work on acclaimed dramas and science-themed films such as "Awakenings" and "WarGames."
-
B.
Lewis L. Lasker
Lewis L. Lasker was a notable figure significant enough in his community or field to have the Lasker Rink named in his honor.
-
C.
Mike Lasker
Mike Lasker is a visual effects supervisor and cinematographer known for his work on the animated film "The Mitchells vs. the Machines."
-
D.
Alex Lasker
Alex Lasker is a screenwriter best known for co-writing the military action film "Tears of the Sun."
-
E.
Reuben Lasker
Reuben Lasker was a prominent American fisheries biologist known for his influential research on fish larvae and marine ecosystems.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d3489dc8190a619c58025dbb250 |
completed | April 19, 2026, 5:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01e82b36448190b3b49b864e987f63 |
completed | May 11, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_6a01ecfb2ff4819082f67ab1f2ce8885 |
completed | May 11, 2026, 2:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01ee0c03e881908aaaa3bd0f596387 |
completed | May 11, 2026, 2:56 p.m. |
Created at: April 10, 2026, 5:51 a.m.