Triple
T7654952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbara Brecht-Schall |
E173355
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | East Berlin |
E25341
|
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: East Berlin | Statement: [Barbara Brecht-Schall, workLocation, East Berlin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: East Berlin Context triple: [Barbara Brecht-Schall, workLocation, East Berlin]
-
A.
East Berlin
chosen
East Berlin was the Soviet-controlled eastern sector of Berlin that served as the capital of East Germany during the Cold War.
-
B.
West Berlin
West Berlin was the Western-aligned, enclave-like portion of Berlin surrounded by East Germany during the Cold War, symbolizing resistance to Soviet pressure and the division of Germany.
-
C.
Berlin Ost
Berlin Ost was the former name of Berlin Ostbahnhof, a major railway station in the eastern part of Berlin, Germany.
-
D.
Berlin
Berlin is a major Ethereum network upgrade that introduced various gas cost optimizations and transaction processing improvements to enhance the blockchain’s efficiency and performance.
-
E.
Berlin
Berlin is a borough in Camden County, New Jersey, known as a suburban community within the Philadelphia metropolitan area.
- 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_69c6995473348190a4f41d110d619a18 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7018d4cdc819092ca297b836190d9 |
completed | March 27, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a21dd3088190bb026de65970a14b |
completed | March 29, 2026, 3:53 a.m. |
Created at: March 27, 2026, 3:59 p.m.