Triple
T3127923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Use This Gospel |
E65340
|
entity |
| Predicate | creditedWriter |
P17913
|
FINISHED |
| Object | Timothy “Tee” Brown |
E330258
|
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: Timothy “Tee” Brown | Statement: [Use This Gospel, creditedWriter, Timothy “Tee” Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Timothy “Tee” Brown Context triple: [Use This Gospel, creditedWriter, Timothy “Tee” Brown]
-
A.
Timothy “Tee” Brown
chosen
Timothy “Tee” Brown is a music producer best known for his work on the Kanye West track “Use This Gospel.”
-
B.
Owen Teague
Owen Teague is an American actor known for his roles in film and television, including appearances in projects like the horror film "It" and various acclaimed TV series.
-
C.
Timothy Edwards
Timothy Edwards was a colonial New England Congregational minister and scholar, best known as the father of theologian Jonathan Edwards.
-
D.
Tucker Martine
Tucker Martine is an American record producer, engineer, and musician known for his innovative work with artists across indie rock, folk, and experimental music.
-
E.
Ryan Brown
Ryan Brown is a film editor known for his work on the movie "Horse Girl."
- 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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada546a6648190bc4bc3e599e6aa95 |
completed | March 8, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b224d860dc819095a864619bc29411 |
completed | March 12, 2026, 2:28 a.m. |
Created at: March 8, 2026, 3:04 p.m.