Triple
T9462387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Blue Angel |
E228180
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Martha Dübber
Martha Dübber was a film editor known for her work on the classic German film "The Blue Angel."
|
E812813
|
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: Martha Dübber | Statement: [The Blue Angel, editedBy, Martha Dübber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martha Dübber Context triple: [The Blue Angel, editedBy, Martha Dübber]
-
A.
Eva Schubach
Eva Schubach is known as a former spouse of Gerhard Schröder, the one-time Chancellor of Germany.
-
B.
Verena Bentele
Verena Bentele is a German former Paralympic biathlete and cross-country skier who became a prominent politician and disability rights advocate.
-
C.
Dagmar Berghoff
Dagmar Berghoff is a prominent German television and radio presenter best known as one of the first and most recognizable news anchors for the ARD Tagesschau.
-
D.
Barbara Scholz
Barbara Scholz is a philosopher of linguistics known for her influential critiques of nativist theories of language acquisition, particularly the poverty of the stimulus argument.
-
E.
Beverley Schäfer
Beverley Schäfer is a South African politician who serves as the Deputy Speaker of the Western Cape Provincial Parliament.
- 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: Martha Dübber Triple: [The Blue Angel, editedBy, Martha Dübber]
Generated description
Martha Dübber was a film editor known for her work on the classic German film "The Blue Angel."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Martha Dübber Target entity description: Martha Dübber was a film editor known for her work on the classic German film "The Blue Angel."
-
A.
Eva Schubach
Eva Schubach is known as a former spouse of Gerhard Schröder, the one-time Chancellor of Germany.
-
B.
Verena Bentele
Verena Bentele is a German former Paralympic biathlete and cross-country skier who became a prominent politician and disability rights advocate.
-
C.
Dagmar Berghoff
Dagmar Berghoff is a prominent German television and radio presenter best known as one of the first and most recognizable news anchors for the ARD Tagesschau.
-
D.
Barbara Scholz
Barbara Scholz is a philosopher of linguistics known for her influential critiques of nativist theories of language acquisition, particularly the poverty of the stimulus argument.
-
E.
Beverley Schäfer
Beverley Schäfer is a South African politician who serves as the Deputy Speaker of the Western Cape Provincial Parliament.
- 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_69ca846fee388190a6ec273fd644b88b |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fcd9794819093c392489d4efbe9 |
completed | April 1, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d189e601508190b116fca9854057bc |
completed | April 4, 2026, 10 p.m. |
| NEDg | Description generation | batch_69d18aee8ef8819080ce061f3d145712 |
completed | April 4, 2026, 10:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d18b34d14881909b8da862c12f8727 |
completed | April 4, 2026, 10:05 p.m. |
Created at: March 30, 2026, 7:53 p.m.