Triple
T586632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Gropius |
E15170
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Dessau |
E102721
|
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: Dessau | Statement: [Walter Gropius, workLocation, Dessau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dessau Context triple: [Walter Gropius, workLocation, Dessau]
-
A.
Dessau
chosen
Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
-
B.
Leipzig
Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
-
C.
Erlangen
Erlangen is a city in northern Bavaria, Germany, known for its university, research institutions, and historical association with mathematician Emmy Noether.
-
D.
Aschersleben
Aschersleben is a historic town in the German state of Saxony-Anhalt, known as one of the oldest documented cities in central Germany.
-
E.
Weimar
Weimar is a historic German city renowned as a center of culture and the arts, associated with figures like Goethe and Schiller and pivotal movements in modern design and architecture.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9bf0cc8190a145ccd6fc501349 |
completed | March 1, 2026, 8:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac5370a97881908916b387ff6b02af |
completed | March 7, 2026, 4:33 p.m. |
Created at: March 1, 2026, 7:33 p.m.