Triple
T5038532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acoustics: Sound Fields and Transducers |
E113486
|
entity |
| Predicate | hasNotableContributor |
P10455
|
FINISHED |
| Object | Tim Mellow |
E487813
|
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: Tim Mellow | Statement: [Acoustics: Sound Fields and Transducers, hasNotableContributor, Tim Mellow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tim Mellow Context triple: [Acoustics: Sound Fields and Transducers, hasNotableContributor, Tim Mellow]
-
A.
Tim Mellow
chosen
Tim Mellow is an acoustics engineer and author known for co-writing the technical reference book "Acoustics: Sound Fields and Transducers."
-
B.
Scott Litt
Scott Litt is an American record producer and engineer best known for his influential work with alternative rock bands such as R.E.M. and Nirvana.
-
C.
Mike Kellin
Mike Kellin was an American character actor known for his prolific work in film, television, and theater from the 1950s through the 1970s.
-
D.
Robby Mook
Robby Mook is an American political strategist best known for serving as campaign manager for Hillary Clinton’s 2016 U.S. presidential campaign.
-
E.
Max Martini
Max Martini is an American actor known for his tough, military and law-enforcement roles in film and television, including major parts in action and science fiction movies.
- 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_69bd44384298819089c49e7c330ec7b8 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73daaa788190b670f6c328bfa44f |
completed | March 20, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb0f21d308190adbac06397f90cee |
completed | March 21, 2026, 2:53 p.m. |
Created at: March 20, 2026, 1:37 p.m.