Triple
T2853099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Britta Ernst |
E63136
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Britta Ernst |
E63136
|
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: Britta Ernst | Statement: [Britta Ernst, name, Britta Ernst]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Britta Ernst Context triple: [Britta Ernst, name, Britta Ernst]
-
A.
Britta Ernst
chosen
Britta Ernst is a German politician of the Social Democratic Party (SPD) who has served as a state minister for education in several German states and is married to Chancellor Olaf Scholz.
-
B.
Johanna Herting
Johanna Herting was the wife of 19th-century civil engineer John A. Roebling, known for supporting him during his career designing pioneering suspension bridges such as the Brooklyn Bridge.
-
C.
Julia Sauer
Julia Sauer was an American librarian and author best known for her atmospheric children's fantasy and historical novels, including the Newbery Honor book "Fog Magic."
-
D.
Ute Grunert
Ute Grunert is known as the spouse of Nobel Prize–winning German author Günter Grass.
-
E.
Sara Esberg
Sara Esberg is a television producer known for her executive production work on series such as the psychological horror show "Swarm."
- 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_69ab4c407c408190857d25e027155ce9 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf5e043c8190ac82112abce7262a |
completed | March 7, 2026, 8:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8e4e0b881908de5c4927609725e |
completed | March 10, 2026, 9:48 a.m. |
Created at: March 6, 2026, 10:02 p.m.