Triple
T5528044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steiner |
E144974
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Steinerová |
E144974
|
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: Steinerová | Statement: [Steiner, hasVariant, Steinerová]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steinerová Context triple: [Steiner, hasVariant, Steinerová]
-
A.
Steiner
chosen
Steiner is a common German-language surname borne by numerous notable individuals across fields such as music, philosophy, and science.
-
B.
Morgenstern
Morgenstern is a German surname borne by various notable figures in fields such as economics, literature, and the arts.
-
C.
Doroteja
Doroteja is a feminine given name, commonly used in Slavic countries, that is a variant of the name Dorothea.
-
D.
Böhme
The Böhme is a river in Lower Saxony, Germany, known for flowing through the Lüneburg Heath region before joining the Aller.
-
E.
Setra
Setra is a German brand of premium coaches and buses known for its high-quality engineering and comfort, produced by Daimler AG.
- 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_69c008f873a481909b4d9f7e2db3c37d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f8b6c348190b7d414dc1907d09a |
completed | March 22, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c027fe1c508190b95b7b5bda96a32d |
completed | March 22, 2026, 5:33 p.m. |
Created at: March 22, 2026, 3:34 p.m.