Triple
T10592277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Best |
E250020
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Dan Hartman |
E699235
|
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: Dan Hartman | Statement: [The Best, producer, Dan Hartman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Hartman Context triple: [The Best, producer, Dan Hartman]
-
A.
Dan Hartman
chosen
Dan Hartman was an American musician, singer, songwriter, and producer best known for his disco and pop hits in the 1970s and 1980s.
-
B.
Allen Ludden
Allen Ludden was an American television personality and game show host best known for hosting the quiz show "Password."
-
C.
Steve Ross
Steve Ross was an American businessman best known for building Warner Communications into a media powerhouse and serving as a key architect of what became Time Warner.
-
D.
John Carson
John Carson is a fictional character appearing in the film "The Miracle Woman."
-
E.
Bill Justis
Bill Justis was an American musician, arranger, and composer best known for his influential work in early rock and roll and pop music, including the hit instrumental "Raunchy."
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5277c79808190acc872919eadd126 |
completed | April 7, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95e85c49c8190a580536be07c0405 |
completed | April 10, 2026, 8:33 p.m. |
Created at: April 6, 2026, 12:40 p.m.