Triple
T9824882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilm Hosenfeld |
E238629
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Thomas Kretschmann |
E21474
|
NE FINISHED |
How this triple was built (2 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: Thomas Kretschmann | Statement: [Wilm Hosenfeld, portrayedBy, Thomas Kretschmann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Kretschmann Context triple: [Wilm Hosenfeld, portrayedBy, Thomas Kretschmann]
-
A.
Thomas Kretschmann
chosen
Thomas Kretschmann is a German actor known for his frequent roles in war and historical films, including notable performances in "The Pianist," "Downfall," and "King Kong."
-
B.
Daniel Günther
Daniel Günther is a German politician from the Christian Democratic Union (CDU) who serves as the Minister-President of the northern federal state of Schleswig-Holstein.
-
C.
Michael Müller
Michael Müller is a German politician from the Social Democratic Party (SPD) who served as the Governing Mayor of Berlin in the 2010s.
-
D.
Peter Kohl
Peter Kohl is a German businessman and author best known as the son of former German Chancellor Helmut Kohl.
-
E.
Christian Scholz
Christian Scholz is a German computer scientist and open-source developer known for his contributions to web technologies and social software.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3181c688190afea3b27ee392a30 |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc810bac8190a5ff94c0717e7706 |
completed | April 5, 2026, 2:44 a.m. |
Created at: March 30, 2026, 8:31 p.m.