Triple
T21250973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robin Hood: Men in Tights |
E523742
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Peter Schindler
Peter Schindler is a film producer best known for his work on the Mel Brooks parody comedy "Robin Hood: Men in Tights."
|
E1492259
|
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 Schindler | Statement: [Robin Hood: Men in Tights, producer, Peter Schindler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Schindler Context triple: [Robin Hood: Men in Tights, producer, Peter Schindler]
-
A.
Peter Schindler
Peter Schindler is a film producer best known for his work on the romantic comedy "Forget Paris."
-
B.
Peter Schilling
Peter Schilling is a German synth-pop musician best known internationally for his 1983 hit single "Major Tom (Coming Home)."
-
C.
Peter Riedler
Peter Riedler is an Austrian academic and university administrator who serves as rector of the University of Graz.
-
D.
Peter Schweger
Peter Schweger is a German architect known for designing prominent contemporary buildings, including major high-rise projects.
-
E.
Peter Scheerer
Peter Scheerer is a German screenwriter and filmmaker known for co-writing genre films such as the horror adaptation "Alone in the Dark" (2005).
- 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 Schindler Triple: [Robin Hood: Men in Tights, producer, Peter Schindler]
Generated description
Peter Schindler is a film producer best known for his work on the Mel Brooks parody comedy "Robin Hood: Men in Tights."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter Schindler Target entity description: Peter Schindler is a film producer best known for his work on the Mel Brooks parody comedy "Robin Hood: Men in Tights."
-
A.
Peter Schindler
Peter Schindler is a film producer best known for his work on the romantic comedy "Forget Paris."
-
B.
Peter Schilling
Peter Schilling is a German synth-pop musician best known internationally for his 1983 hit single "Major Tom (Coming Home)."
-
C.
Peter Riedler
Peter Riedler is an Austrian academic and university administrator who serves as rector of the University of Graz.
-
D.
Peter Schweger
Peter Schweger is a German architect known for designing prominent contemporary buildings, including major high-rise projects.
-
E.
Peter Scheerer
Peter Scheerer is a German screenwriter and filmmaker known for co-writing genre films such as the horror adaptation "Alone in the Dark" (2005).
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7359e90d881909b3153f1e7213c5c |
completed | April 21, 2026, 8:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09fd1bb8c48190a2f9dff6a0c2eaeb |
completed | May 17, 2026, 5:38 p.m. |
| NEDg | Description generation | batch_6a09fdf8a3f08190b3e1cf046920584d |
completed | May 17, 2026, 5:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09fe7982748190ab3f61e7c2dc32ae |
completed | May 17, 2026, 5:44 p.m. |
Created at: April 16, 2026, 3:56 p.m.