Triple
T267840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolregion Mitteldeutschland |
E5771
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Jena |
E60682
|
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: Jena | Statement: [Metropolregion Mitteldeutschland, hasMember, Jena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jena Context triple: [Metropolregion Mitteldeutschland, hasMember, Jena]
-
A.
Jena
chosen
Jena is a historic university city in the German state of Thuringia, known for its role in optics, philosophy, and science.
-
B.
Leipzig
Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
-
C.
Dresden
Dresden is a historic cultural and economic center in eastern Germany, renowned for its baroque architecture, art collections, and reconstruction after World War II.
-
D.
Karlsruhe
Karlsruhe is a major city in southwestern Germany best known as the seat of the country’s highest courts and a central hub of German constitutional jurisprudence.
-
E.
Heidelberg
Heidelberg is a historic university city in southwestern Germany renowned for its picturesque old town, castle ruins, and one of Europe’s oldest universities.
- 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_69a6891458408190a01baf3f2e118ac5 |
completed | March 3, 2026, 7:09 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.