Triple
T11768758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Lindner |
E279843
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Christian Lindner |
E279843
|
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: Christian Lindner | Statement: [Christian Lindner, name, Christian Lindner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christian Lindner Context triple: [Christian Lindner, name, Christian Lindner]
-
A.
Christian Lindner
chosen
Christian Lindner is a German politician who serves as the federal minister of finance and is a leading figure in Germany’s liberal political camp.
-
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.
Christian Scholz
Christian Scholz is a German computer scientist and open-source developer known for his contributions to web technologies and social software.
-
D.
Sigmar Gabriel
Sigmar Gabriel is a German Social Democratic politician who has served in prominent national roles including Vice Chancellor and Federal Minister for Foreign Affairs.
-
E.
Thomas Kretschmann
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."
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a526979c8190ad2089997906855b |
completed | April 10, 2026, 7:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f09075aba8819082434a43473025bd |
completed | April 28, 2026, 10:48 a.m. |
Created at: April 8, 2026, 9:41 p.m.