Triple
T10494002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raising Cain |
E247487
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Steven Bauer |
E599197
|
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: Steven Bauer | Statement: [Raising Cain, starring, Steven Bauer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steven Bauer Context triple: [Raising Cain, starring, Steven Bauer]
-
A.
Steven Bauer
chosen
Steven Bauer is a Cuban-American actor best known for his role as Manny Ribera in the film "Scarface" and for numerous supporting roles in film and television.
-
B.
Steven Baigelman
Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
-
C.
Richard Baskin
Richard Baskin is an American composer and music producer best known for his film scores and work in the 1970s and 1980s, particularly in Hollywood.
-
D.
Kevin Westenberg
Kevin Westenberg is a renowned portrait and music photographer known for his striking images of prominent musicians and entertainers.
-
E.
Alan Siegel
Alan Siegel is a film producer best known for his long-running collaboration with actor Gerard Butler on action and thriller movies.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5097fe2bc81909d66ce43f3533284 |
completed | April 7, 2026, 1:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbb6db3f2c81908a7cb28ca8e8ebc9 |
completed | April 12, 2026, 3:14 p.m. |
Created at: April 6, 2026, 12:24 p.m.