Triple
T16672228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smoke & Mirrors |
E405132
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | John Fields |
E1105417
|
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: John Fields | Statement: [Smoke & Mirrors, producer, John Fields]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Fields Context triple: [Smoke & Mirrors, producer, John Fields]
-
A.
John Fields
chosen
John Fields is an American record producer and musician known for his work with pop and rock artists such as the Jonas Brothers, Demi Lovato, and Switchfoot.
-
B.
Jack Fields
Jack Fields was the first husband of American actress and television producer Whitney Blake.
-
C.
Joseph Fields
Joseph Fields was an American playwright, screenwriter, and producer known for his work on Broadway and in Hollywood during the mid-20th century.
-
D.
Allan Felder
Allan Felder was an American songwriter and producer best known for his work in 1970s soul and R&B, particularly with the Philadelphia soul sound.
-
E.
Robert Fields
Robert Fields is an American actor best known for his role in the 1969 film "They Shoot Horses, Don't They?"
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ca175088190a0435422e13278c2 |
completed | April 18, 2026, 12:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a3916508190bd5edd91310ddb5a |
completed | May 10, 2026, 1:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.