Triple
T16133798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fitzcarraldo |
E391469
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Beate Mainka-Jellinghaus
Beate Mainka-Jellinghaus is a German film editor best known for her long-standing collaboration with director Werner Herzog on many of his acclaimed films.
|
E1195426
|
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: Beate Mainka-Jellinghaus | Statement: [Fitzcarraldo, editedBy, Beate Mainka-Jellinghaus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beate Mainka-Jellinghaus Context triple: [Fitzcarraldo, editedBy, Beate Mainka-Jellinghaus]
-
A.
Birgit Menzel
Birgit Menzel is a scholar and academic known for her work in Slavic studies and Russian literature and culture.
-
B.
Adelheid Wendt
Adelheid Wendt was the mother of renowned German conductor and composer Wilhelm Furtwängler.
-
C.
Roswitha Eberl
Roswitha Eberl is a former East German sprint canoer who won multiple Olympic gold medals in the late 1970s and early 1980s.
-
D.
Helga Timmermann
Helga Timmermann is an architect known for her work on the Kollhoff Tower in Berlin.
-
E.
Helga Maria Betten
Helga Maria Betten is known as the wife of acclaimed German cinematographer Michael Ballhaus.
- 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: Beate Mainka-Jellinghaus Triple: [Fitzcarraldo, editedBy, Beate Mainka-Jellinghaus]
Generated description
Beate Mainka-Jellinghaus is a German film editor best known for her long-standing collaboration with director Werner Herzog on many of his acclaimed films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Beate Mainka-Jellinghaus Target entity description: Beate Mainka-Jellinghaus is a German film editor best known for her long-standing collaboration with director Werner Herzog on many of his acclaimed films.
-
A.
Birgit Menzel
Birgit Menzel is a scholar and academic known for her work in Slavic studies and Russian literature and culture.
-
B.
Adelheid Wendt
Adelheid Wendt was the mother of renowned German conductor and composer Wilhelm Furtwängler.
-
C.
Roswitha Eberl
Roswitha Eberl is a former East German sprint canoer who won multiple Olympic gold medals in the late 1970s and early 1980s.
-
D.
Helga Timmermann
Helga Timmermann is an architect known for her work on the Kollhoff Tower in Berlin.
-
E.
Helga Maria Betten
Helga Maria Betten is known as the wife of acclaimed German cinematographer Michael Ballhaus.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a039f0c8190a679e16a27f2dbe3 |
completed | April 17, 2026, 11:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2b1b7248190a1bba4a87db8318b |
completed | May 10, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_69fff3478bfc8190bbcc0afbf6dbb089 |
completed | May 10, 2026, 2:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fff3d29f50819093a9355d016f48dd |
completed | May 10, 2026, 2:56 a.m. |
Created at: April 10, 2026, 5:01 a.m.