Triple
T267842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolregion Mitteldeutschland |
E5771
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Gera |
E22181
|
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: Gera | Statement: [Metropolregion Mitteldeutschland, hasMember, Gera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gera Context triple: [Metropolregion Mitteldeutschland, hasMember, Gera]
-
A.
Gera
chosen
Gera is a city in the German state of Thuringia, known for its industrial heritage and historic architecture along the White Elster river.
-
B.
Leven
Leven is a coastal town in eastern Scotland, situated on the Firth of Forth in the council area of Fife.
-
C.
Hesse
Hesse is a federal state in central Germany known for its financial hub Frankfurt am Main and its mix of urban centers, forests, and historic towns.
-
D.
Chemnitz River
The Chemnitz River is a waterway in the German state of Saxony that flows through and gives its name to the city of Chemnitz.
-
E.
Elbe
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.
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25dae4a0c8190a66cf6ed3889851c |
completed | Feb. 28, 2026, 3:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3a336d8b08190988eaf39f950f8cd |
completed | March 1, 2026, 2:23 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.