Triple
T3066769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Life and Death of Peter Sellers |
E62120
|
entity |
| Predicate | cinematographer |
P1953
|
FINISHED |
| Object |
Peter Levy
Peter Levy is a cinematographer known for his work on films such as "The Life and Death of Peter Sellers."
|
E328112
|
NE FINISHED |
How this triple was built (4 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: Peter Levy | Statement: [The Life and Death of Peter Sellers, cinematographer, Peter Levy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Levy Context triple: [The Life and Death of Peter Sellers, cinematographer, Peter Levy]
-
A.
David Levy
David Levy is a film producer known for his work on the acclaimed British mystery drama "Gosford Park."
-
B.
Philip Brenner
Philip Brenner is a scholar and author known for his work on U.S. foreign policy and Latin American studies, often collaborating with historian James G. Blight.
-
C.
David F. Levi
David F. Levi is an American legal scholar and former federal judge who served as dean of Duke University School of Law.
-
D.
Philip Brownstein
Philip Brownstein was a professional basketball coach best known for leading the early NBA-era Chicago Stags franchise.
-
E.
Michele Lerner
Michele Lerner is known primarily as the third wife of American lyricist and playwright Alan Jay Lerner.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Peter Levy Triple: [The Life and Death of Peter Sellers, cinematographer, Peter Levy]
Generated description
Peter Levy is a cinematographer known for his work on films such as "The Life and Death of Peter Sellers."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter Levy Target entity description: Peter Levy is a cinematographer known for his work on films such as "The Life and Death of Peter Sellers."
-
A.
David Levy
David Levy is a film producer known for his work on the acclaimed British mystery drama "Gosford Park."
-
B.
Philip Brenner
Philip Brenner is a scholar and author known for his work on U.S. foreign policy and Latin American studies, often collaborating with historian James G. Blight.
-
C.
David F. Levi
David F. Levi is an American legal scholar and former federal judge who served as dean of Duke University School of Law.
-
D.
Philip Brownstein
Philip Brownstein was a professional basketball coach best known for leading the early NBA-era Chicago Stags franchise.
-
E.
Michele Lerner
Michele Lerner is known primarily as the third wife of American lyricist and playwright Alan Jay Lerner.
- F. None of above. chosen
Provenance (5 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada0fd87308190918e7b616f033faa |
completed | March 8, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2035055148190ad1cdd6374820e60 |
completed | March 12, 2026, 12:05 a.m. |
| NEDg | Description generation | batch_69b207593cb8819091203b3738fa69db |
completed | March 12, 2026, 12:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2083329cc8190a88bfa39d7572317 |
completed | March 12, 2026, 12:26 a.m. |
Created at: March 8, 2026, 3:02 p.m.