Triple
T14526568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phoebe Snow |
E340792
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Donald Fagen |
E1053622
|
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: Donald Fagen | Statement: [Phoebe Snow, associatedAct, Donald Fagen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donald Fagen Context triple: [Phoebe Snow, associatedAct, Donald Fagen]
-
A.
Donald Fagen
chosen
Donald Fagen is an American musician, singer, and songwriter best known as the co-founder, lead vocalist, and keyboardist of the jazz-rock band Steely Dan.
-
B.
Greg Morrisett
Greg Morrisett is a computer scientist known for his work on programming languages and type systems, particularly in the design of safe and secure systems.
-
C.
Mike Garfath
Mike Garfath is a cinematographer best known for his work on the British neo-noir film "Croupier."
-
D.
Walter Becker
Walter Becker was an American musician, songwriter, and record producer best known as the co-founder, guitarist, and bassist of the jazz-rock band Steely Dan.
-
E.
Michael Franks
Michael Franks is an American jazz and soft rock singer-songwriter known for his smooth vocal style and sophisticated, often witty lyrics.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea050781881909ed685d94479bf99 |
completed | April 14, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a52260881909a0d85603666107d |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:22 a.m.