Triple
T10475482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ctrl |
E247035
|
entity |
| Predicate | hasProducer |
P30366
|
FINISHED |
| Object | Teddy Walton |
E861783
|
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: Teddy Walton | Statement: [Ctrl, hasProducer, Teddy Walton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teddy Walton Context triple: [Ctrl, hasProducer, Teddy Walton]
-
A.
Teddy Walton
chosen
Teddy Walton is an American record producer known for his atmospheric, genre-blending hip-hop and R&B work with artists like Kendrick Lamar, Bryson Tiller, and A$AP Rocky.
-
B.
Wallace Woods
Wallace Woods is a historic residential neighborhood in Covington, Kentucky, known for its early 20th-century architecture and tree-lined streets.
-
C.
Teddy Maynard
Teddy Maynard is a powerful, terminally ill CIA spymaster who secretly orchestrates events behind the scenes in John Grisham’s novel "The Broker."
-
D.
Teddy Bishop
Teddy Bishop is a music producer known for his work in R&B and gospel, including collaborations with prominent artists and contributions to contemporary soul-influenced records.
-
E.
Tom Tully
Tom Tully was an American character actor known for his prolific work in mid-20th-century film and television, often portraying gruff but sympathetic authority figures.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5094f6b408190a5a26b1a82e4a02b |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8a01d8b888190a9137b104f0e0c0c |
completed | April 10, 2026, 7 a.m. |
Created at: April 6, 2026, 12:21 p.m.