Triple
T5151615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saale |
E116207
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Naumburg |
E210567
|
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: Naumburg | Statement: [Saale, flowsThrough, Naumburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naumburg Context triple: [Saale, flowsThrough, Naumburg]
-
A.
Naumburg
chosen
Naumburg is a historic town in the German state of Saxony-Anhalt, known for its medieval cathedral and as the childhood home of philosopher Friedrich Nietzsche.
-
B.
Nordhausen
Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
-
C.
Halberstadt
Halberstadt is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and role as a former episcopal seat.
-
D.
Schmalkalden
Schmalkalden is a historic town in the German state of Thuringia, known for its well-preserved medieval architecture and role in Reformation-era politics.
-
E.
Ilmenau
Ilmenau is a German town best known for its location in the Thuringian Forest and its association with the poet Johann Wolfgang von Goethe.
- 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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd78d965548190b09f574acf3b9b1a |
completed | March 20, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef7f117ac8190a03379437484627b |
completed | March 21, 2026, 7:56 p.m. |
Created at: March 20, 2026, 1:44 p.m.