Triple
T3688033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mulde |
E78272
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Wurzen |
E289633
|
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: Wurzen | Statement: [Mulde, flowsThrough, Wurzen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wurzen Context triple: [Mulde, flowsThrough, Wurzen]
-
A.
Wurzen
chosen
Wurzen is a historic town in the German state of Saxony, known for its medieval architecture and location on the river Mulde east of Leipzig.
-
B.
Werdau
Werdau is a town in the Free State of Saxony in eastern Germany, historically known for its textile and engineering industries.
-
C.
Döbeln
Döbeln is a small town in the German state of Saxony, known for its historic center and location between the cities of Leipzig, Dresden, and Chemnitz.
-
D.
Bautzen
Bautzen is a historic town in eastern Germany known for its well-preserved medieval architecture and as a cultural center of the Sorbian minority.
-
E.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
- 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_69ad85e285a081908f8cbfa9e2ed9b75 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4c960788190b73ede08658846aa |
completed | March 8, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bda3f5a8a88190a494a9338c01962a |
completed | March 20, 2026, 7:45 p.m. |
Created at: March 8, 2026, 3:26 p.m.