Triple
T15914161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goner Records |
E385926
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Eric Friedl
Eric Friedl is an American musician and independent record label founder best known for creating the influential Memphis-based punk and garage rock label Goner Records.
|
E1182669
|
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: Eric Friedl | Statement: [Goner Records, foundedBy, Eric Friedl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eric Friedl Context triple: [Goner Records, foundedBy, Eric Friedl]
-
A.
Jeff Friedl
Jeff Friedl is an American drummer best known for his work with alternative rock and industrial bands, including his role in Devo’s later lineups.
-
B.
David Flanagan
David Flanagan is a software developer and technical author best known for his widely used programming books, including "JavaScript: The Definitive Guide."
-
C.
David Heitner
David Heitner is a film editor known for his work on the South African musical drama film "Sarafina!".
-
D.
Michael Kaplan
Michael Kaplan is a composer and musician known for creating the music for the film "Burlesque."
-
E.
Michael Feathers
Michael Feathers is a software engineer, consultant, and author known for his influential work on legacy code, refactoring, and improving software design and maintainability.
- 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: Eric Friedl Triple: [Goner Records, foundedBy, Eric Friedl]
Generated description
Eric Friedl is an American musician and independent record label founder best known for creating the influential Memphis-based punk and garage rock label Goner Records.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eric Friedl Target entity description: Eric Friedl is an American musician and independent record label founder best known for creating the influential Memphis-based punk and garage rock label Goner Records.
-
A.
Jeff Friedl
Jeff Friedl is an American drummer best known for his work with alternative rock and industrial bands, including his role in Devo’s later lineups.
-
B.
David Flanagan
David Flanagan is a software developer and technical author best known for his widely used programming books, including "JavaScript: The Definitive Guide."
-
C.
David Heitner
David Heitner is a film editor known for his work on the South African musical drama film "Sarafina!".
-
D.
Michael Kaplan
Michael Kaplan is a composer and musician known for creating the music for the film "Burlesque."
-
E.
Michael Feathers
Michael Feathers is a software engineer, consultant, and author known for his influential work on legacy code, refactoring, and improving software design and maintainability.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15661046c819097a53de2a3e0443b |
completed | April 16, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb0592b5c8190a4597644864a6bcb |
completed | May 9, 2026, 10:08 p.m. |
| NEDg | Description generation | batch_69ffb0ef7f3081908744a759bb3e4e8c |
completed | May 9, 2026, 10:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb1dbd7d08190b84ae201e0866139 |
completed | May 9, 2026, 10:14 p.m. |
Created at: April 10, 2026, 4:52 a.m.