Triple
T8613194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bard College Berlin |
E203965
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Niederschönhausen |
E412020
|
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: Niederschönhausen | Statement: [Bard College Berlin, locatedIn, Niederschönhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niederschönhausen Context triple: [Bard College Berlin, locatedIn, Niederschönhausen]
-
A.
Niederschönhausen
chosen
Niederschönhausen is a residential district in the Berlin borough of Pankow, known for its historic villas, green spaces, and the former presidential residence Schloss Schönhausen.
-
B.
Niederschöneweide
Niederschöneweide is a locality in the Berlin borough of Treptow-Köpenick, known for its riverside setting along the Spree and its mix of residential areas and former industrial sites.
-
C.
Schönewalde
Schönewalde is a town in the state of Brandenburg, Germany, known for hosting a German Air Force base.
-
D.
Hohen Neuendorf
Hohen Neuendorf is a town in the German state of Brandenburg, located just north of Berlin and known as a residential suburb with access to the capital.
-
E.
Hasselwerder
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
- 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_69ca832c23e4819095a9f3eea4a21828 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46fdf21c81908ffc6363e98ab871 |
completed | March 31, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebbc1d8a08190bbcf7c4cef0fe04d |
completed | April 2, 2026, 6:56 p.m. |
Created at: March 30, 2026, 6:25 p.m.