Triple
T17984546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grunewaldstraße |
E430192
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Grunewald |
—
|
NE NERFINISHED |
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: Grunewald | Statement: [Grunewaldstraße, namedAfter, Grunewald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grunewald Context triple: [Grunewaldstraße, namedAfter, Grunewald]
-
A.
Grunewald
chosen
Grunewald is a forested, upscale district in western Berlin known for its large woodland area, lakes, and villas.
-
B.
Grunewald forest
Grunewald forest is a large woodland and recreational area in western Berlin, known for its lakes, walking trails, and natural landscapes.
-
C.
Matthias Grünewald
Matthias Grünewald was a German painter renowned for his intensely emotional and expressive religious works, most famously the Isenheim Altarpiece, which stand out within the Northern Renaissance for their dramatic color and visionary imagery.
-
D.
Isenheim
Isenheim is a town in the Alsace region of northeastern France historically known for the monastery that housed the famous Isenheim Altarpiece.
-
E.
Creutzwald
Creutzwald is a small industrial town in northeastern France near the German border, known historically for its coal mining and glassmaking industries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29a27b081909a128a6b978eabf8 |
completed | April 19, 2026, 10:46 a.m. |
Created at: April 10, 2026, 10:23 a.m.