Triple
T686867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roter Turm (Chemnitz) |
E13302
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Markt Chemnitz |
E1679
|
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: Markt Chemnitz | Statement: [Roter Turm (Chemnitz), locatedNear, Markt Chemnitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Markt Chemnitz Context triple: [Roter Turm (Chemnitz), locatedNear, Markt Chemnitz]
-
A.
Grüner Markt
Grüner Markt is a central marketplace and public square in the Bavarian city of Fürth, known for its local vendors and historic urban setting.
-
B.
Chemnitz
chosen
Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
-
C.
Kunstsammlungen Chemnitz
Kunstsammlungen Chemnitz is a major German museum complex in Chemnitz known for its extensive collections of fine art and cultural history.
-
D.
Görlitz
Görlitz is a historic city in eastern Germany on the Lusatian Neisse River, known for its well-preserved old town and role as a popular film location.
-
E.
Chemnitz Hauptbahnhof
Chemnitz Hauptbahnhof is the main railway station and central transportation hub of the city of Chemnitz in Saxony, Germany.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a093ac988190bb339616a3ed5adb |
completed | March 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a6374ee9ac819091abef4167e3433e |
completed | March 3, 2026, 1:20 a.m. |
Created at: March 1, 2026, 7:36 p.m.