Triple
T14384697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Count of Monte Cristo (2002 film) |
E356692
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Stephen Semel |
E757316
|
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: Stephen Semel | Statement: [The Count of Monte Cristo (2002 film), editor, Stephen Semel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stephen Semel Context triple: [The Count of Monte Cristo (2002 film), editor, Stephen Semel]
-
A.
Stephen Semel
chosen
Stephen Semel is an American film and television editor known for his work on various feature films and TV series.
-
B.
Brad Segal
Brad Segal is a composer and musician best known for creating film scores, including the soundtrack for the teen comedy "Easy A."
-
C.
Todd Lieberman
Todd Lieberman is an American film producer known for his work on acclaimed movies such as "The Fighter" and other major Hollywood productions.
-
D.
Greg Shapiro
Greg Shapiro is an American film producer best known for his Academy Award-winning work on "The Hurt Locker" and other notable independent and studio films.
-
E.
Jeremy Kleiner
Jeremy Kleiner is an American film producer known for his work on acclaimed films such as the civil rights drama "Selma."
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9025cff881908c08224d90d9f750 |
completed | April 14, 2026, 7:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5513e8888190bc6b6cb33fd9b670 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:16 a.m.