Triple
T20820261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Buscema |
E512555
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Sal Buscema |
—
|
NE NERFINISHED |
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: Sal Buscema | Statement: [John Buscema, sibling, Sal Buscema]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sal Buscema Context triple: [John Buscema, sibling, Sal Buscema]
-
A.
Sal Buscema
chosen
Sal Buscema is an American comic book artist best known for his long, influential runs on Marvel titles such as The Incredible Hulk, The Avengers, and Spectacular Spider-Man.
-
B.
Paul Hirsch
Paul Hirsch is an American film editor renowned for his work on major Hollywood films, including the original Star Wars.
-
C.
Paul Hirsch
Paul Hirsch was a German Social Democratic politician who briefly served as Minister President of Prussia during the early Weimar Republic.
-
D.
Arthur Hiller
Arthur Hiller was a Canadian-born film director best known for popular Hollywood movies such as "Love Story" and "The In-Laws."
-
E.
Alfred Cox
Alfred Cox was an architect known for designing Kingston Museum in Kingston upon Thames, England.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2f6a65481909a0df78616e185e4 |
completed | April 21, 2026, 12:21 a.m. |
Created at: April 16, 2026, 12:41 p.m.