Triple
T6415409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fat Wreck Chords |
E127814
|
entity |
| Predicate | hasFounder |
P104
|
FINISHED |
| Object | Erin Burkett |
E652562
|
NE FINISHED |
How this triple was built (2 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: Erin Burkett | Statement: [Fat Wreck Chords, hasFounder, Erin Burkett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erin Burkett Context triple: [Fat Wreck Chords, hasFounder, Erin Burkett]
-
A.
Erin Burkett
chosen
Erin Burkett is an American music industry executive and co-founder of the influential punk rock record label Fat Wreck Chords.
-
B.
Erin Daniels
Erin Daniels is an American actress best known for her role as Dana Fairbanks on the television drama series "The L Word."
-
C.
Erin Walton
Erin Walton is a central daughter in the Walton family on the classic American television series "The Waltons," known for her sensitivity, ambition, and evolving independence.
-
D.
Erin Kelley
Erin Kelley is a lively main character known for her passion for music and her love of dancing.
-
E.
Erin McDermott
Erin McDermott is a collegiate sports administrator best known as the athletic director at Harvard University.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c0083815208190a9b299b8e0640218 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c068e6bd3881909b1979de5cdf17fb |
completed | March 22, 2026, 10:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e4f308048190a5c42022e3f9e855 |
completed | March 28, 2026, 2:25 p.m. |
Created at: March 22, 2026, 4:42 p.m.