Triple
T1453339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glienicke Bridge |
E31341
|
entity |
| Predicate | separates |
P1175
|
FINISHED |
| Object | Berlin |
E5567
|
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: Berlin | Statement: [Glienicke Bridge, separates, Berlin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berlin Context triple: [Glienicke Bridge, separates, Berlin]
-
A.
Berlin
chosen
Berlin is the capital and largest city of Germany, historically significant as a focal point of Cold War tensions and a major cultural, political, and economic center in Europe.
-
B.
Berlin
Berlin is a charismatic, calculating, and morally ambiguous mastermind and heist leader in the Spanish television series "Money Heist" (La Casa de Papel).
-
C.
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.
-
D.
East Berlin
East Berlin was the Soviet-controlled eastern sector of Berlin that served as the capital of East Germany during the Cold War.
-
E.
Berlin Gesundbrunnen
Berlin Gesundbrunnen is a major railway and transport hub in northern Berlin, serving regional, long-distance, and S-Bahn trains as well as local U-Bahn and bus connections.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c57e82d48190a30a4512f39f5de0 |
completed | March 1, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4005cd4c81909cff0ed6529d1695 |
completed | March 8, 2026, 9:23 a.m. |
Created at: March 1, 2026, 8 p.m.