Triple
T1226327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empire |
E26334
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Jim Beanz |
E141262
|
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: Jim Beanz | Statement: [Empire, composer, Jim Beanz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jim Beanz Context triple: [Empire, composer, Jim Beanz]
-
A.
Jim Beanz
chosen
Jim Beanz is an American songwriter, vocal producer, and record producer known for his extensive work with Timbaland and contributions to numerous R&B and pop hits.
-
B.
Sam Beard
Sam Beard is a social entrepreneur and public service advocate best known for co-founding the Jefferson Awards for Public Service, which honor outstanding community and volunteer efforts across the United States.
-
C.
Brian VanDeMark
Brian VanDeMark is an American historian and author known for his work on U.S. foreign policy and the Vietnam War, including coauthoring influential studies of that conflict.
-
D.
Brian Jegan
Brian Jegan is an athlete best known for lighting the ceremonial torch at the 1998 Commonwealth Games.
-
E.
Jim Beaver
Jim Beaver is an American character actor and writer best known for his roles in television series like "Deadwood" and "Supernatural," as well as numerous film appearances.
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be39908481908cca21aaf0828415 |
completed | March 1, 2026, 10:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8f7391408190928cab62e34aa361 |
completed | March 7, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:47 p.m.