Triple
T22366631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 13 Minutes |
E552921
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Oliver Schündler
Oliver Schündler is a German film producer known for his work on historical and dramatic feature films, including the World War II thriller "13 Minutes."
|
E1532306
|
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: Oliver Schündler | Statement: [13 Minutes, producer, Oliver Schündler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oliver Schündler Context triple: [13 Minutes, producer, Oliver Schündler]
-
A.
Oliver Günther
Oliver Günther is a German computer scientist and academic who serves as the president (rector) of the University of Potsdam.
-
B.
Oliver Korittke
Oliver Korittke is a German actor known for his roles in film and television, particularly in comedies and crime series.
-
C.
Oliver Kassman
Oliver Kassman is a film producer known for his work on the psychological horror film "Love Lies Bleeding."
-
D.
Oliver Kellhammer
Oliver Kellhammer is a Canadian-born ecological artist, writer, and educator known for his socially engaged land-based art and environmental restoration projects.
-
E.
Jonas Schneider
Jonas Schneider is a researcher in reinforcement learning best known for co-authoring the Hindsight Experience Replay technique for more efficient learning from sparse rewards.
- 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: Oliver Schündler Triple: [13 Minutes, producer, Oliver Schündler]
Generated description
Oliver Schündler is a German film producer known for his work on historical and dramatic feature films, including the World War II thriller "13 Minutes."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oliver Schündler Target entity description: Oliver Schündler is a German film producer known for his work on historical and dramatic feature films, including the World War II thriller "13 Minutes."
-
A.
Oliver Günther
Oliver Günther is a German computer scientist and academic who serves as the president (rector) of the University of Potsdam.
-
B.
Oliver Korittke
Oliver Korittke is a German actor known for his roles in film and television, particularly in comedies and crime series.
-
C.
Oliver Kassman
Oliver Kassman is a film producer known for his work on the psychological horror film "Love Lies Bleeding."
-
D.
Oliver Kellhammer
Oliver Kellhammer is a Canadian-born ecological artist, writer, and educator known for his socially engaged land-based art and environmental restoration projects.
-
E.
Jonas Schneider
Jonas Schneider is a researcher in reinforcement learning best known for co-authoring the Hindsight Experience Replay technique for more efficient learning from sparse rewards.
- 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_69e11e4affcc8190ba7c27d29062558d |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1580074dc819091305ac7017000d3 |
completed | April 29, 2026, 12:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ae065f01481909ddf2c27e2b471bf |
completed | May 18, 2026, 9:48 a.m. |
| NEDg | Description generation | batch_6a0ae16a8bcc8190852dd17f9c780123 |
completed | May 18, 2026, 9:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ae1e16fac8190b0b56d00a87d173f |
completed | May 18, 2026, 9:54 a.m. |
Created at: April 16, 2026, 8:44 p.m.