Triple
T2151963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Onward |
E47799
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Jeff Danna |
E255691
|
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: Jeff Danna | Statement: [Onward, musicBy, Jeff Danna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Danna Context triple: [Onward, musicBy, Jeff Danna]
-
A.
Jeff Danna
chosen
Jeff Danna is a Canadian film composer known for his scores for movies such as The Boondock Saints and various animated and dramatic films.
-
B.
David Denman
David Denman is an American actor best known for his role as Roy Anderson on the U.S. version of "The Office" and for supporting performances in films and television series across comedy and drama.
-
C.
Dan Dierdorf
Dan Dierdorf is a Hall of Fame American football offensive lineman and longtime broadcaster best known for his standout career with the NFL’s St. Louis Cardinals.
-
D.
Dan Frank
Dan Frank was an influential American book editor known for shaping contemporary literary fiction and nonfiction during his long tenure at major publishing houses.
-
E.
Johnny Gandelsman
Johnny Gandelsman is a Grammy-winning violinist and producer known for his work with ensembles like Brooklyn Rider and the Silk Road Ensemble, as well as for his innovative solo projects.
- 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe48ad148190a7d6cc88fd38a660 |
completed | March 7, 2026, 5:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afb66209bc8190aa030b147e4d34cb |
completed | March 10, 2026, 6:12 a.m. |
Created at: March 4, 2026, 7:44 p.m.