Triple
T3927604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schwarze Elster |
E93313
|
entity |
| Predicate | mouthOfWaterBody |
P3817
|
FINISHED |
| Object | Elbe |
E16410
|
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: Elbe | Statement: [Schwarze Elster, mouthOfWaterBody, Elbe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elbe Context triple: [Schwarze Elster, mouthOfWaterBody, Elbe]
-
A.
Elbe
chosen
The Elbe is one of Central Europe's major rivers, flowing from the Czech Republic through Germany to the North Sea and serving as an important waterway for transport, industry, and agriculture.
-
B.
Saale
The Saale is a major river in central Germany that flows through the states of Thuringia, Saxony-Anhalt, and Bavaria before joining the Elbe.
-
C.
Weser
The Weser is a major river in northwestern Germany that flows through several federal states before emptying into the North Sea.
-
D.
Rhine
The Rhine is one of Europe's most important rivers, historically serving as a vital trade route and cultural boundary from the Alps through Germany to the North Sea.
-
E.
Alte Donau
Alte Donau is a former branch of the Danube River in Vienna that now serves as a popular recreational lake for swimming, boating, and waterside leisure.
- 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_69aed96bfa1081908f7b30f2c647dee6 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeeda4f9d481908dda1b5a826ab64d |
completed | March 9, 2026, 3:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdc51a7c6081909eeda563a4485e87 |
completed | March 20, 2026, 10:07 p.m. |
Created at: March 9, 2026, 3:23 p.m.