Triple
T13995915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | On Your Radar |
E336695
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Fred Falke
Fred Falke is a French house producer and DJ known for his melodic, disco-influenced electronic music and influential remixes.
|
E1074202
|
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: Fred Falke | Statement: [On Your Radar, producer, Fred Falke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fred Falke Context triple: [On Your Radar, producer, Fred Falke]
-
A.
Larry Bryggman
Larry Bryggman is an American actor best known for his long-running role on the soap opera "As the World Turns" and various film and television appearances.
-
B.
Ben Fankhauser
Ben Fankhauser is an American stage actor and singer best known for originating the role of Davey in the Broadway production of the musical "Newsies."
-
C.
Fred Rister
Fred Rister was a French DJ and record producer best known for his frequent collaborations with David Guetta on international dance-pop hits.
-
D.
George Hansen
George Hansen is a fictional character from the 1958 Western film "Terror in a Texas Town."
-
E.
Thomas Heggen
Thomas Heggen was an American author best known for his World War II–era novel "Mister Roberts," which became a hugely successful play and film.
- 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: Fred Falke Triple: [On Your Radar, producer, Fred Falke]
Generated description
Fred Falke is a French house producer and DJ known for his melodic, disco-influenced electronic music and influential remixes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fred Falke Target entity description: Fred Falke is a French house producer and DJ known for his melodic, disco-influenced electronic music and influential remixes.
-
A.
Larry Bryggman
Larry Bryggman is an American actor best known for his long-running role on the soap opera "As the World Turns" and various film and television appearances.
-
B.
Ben Fankhauser
Ben Fankhauser is an American stage actor and singer best known for originating the role of Davey in the Broadway production of the musical "Newsies."
-
C.
Fred Rister
Fred Rister was a French DJ and record producer best known for his frequent collaborations with David Guetta on international dance-pop hits.
-
D.
George Hansen
George Hansen is a fictional character from the 1958 Western film "Terror in a Texas Town."
-
E.
Thomas Heggen
Thomas Heggen was an American author best known for his World War II–era novel "Mister Roberts," which became a hugely successful play and film.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb53f508190855cd69b8061dd77 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac9d4a54819091c7efbeb4dcc5f7 |
completed | May 6, 2026, 9:03 p.m. |
| NEDg | Description generation | batch_69fbadc6cb2c8190bdf66ad1fa6dd392 |
completed | May 6, 2026, 9:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fbb01071408190a85e5e9be0150593 |
completed | May 6, 2026, 9:18 p.m. |
Created at: April 9, 2026, 10:19 p.m.