Triple
T11133302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unstrut |
E263342
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Sömmerda |
E722431
|
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: Sömmerda | Statement: [Unstrut, flowsThrough, Sömmerda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sömmerda Context triple: [Unstrut, flowsThrough, Sömmerda]
-
A.
Sömmerda
chosen
Sömmerda is a town in the German state of Thuringia, known historically for its industrial development and location on the Unstrut River.
-
B.
Trakehnen
Trakehnen was a renowned East Prussian stud farm and village, historically famous as the cradle of the Trakehner horse breed.
-
C.
Haldensleben
Haldensleben is a town in the German state of Saxony-Anhalt, known as an administrative and economic center with historical roots dating back to the Middle Ages.
-
D.
Rudolstadt
Rudolstadt is a historic town in the German state of Thuringia, known for its picturesque old town, Heidecksburg Castle, and cultural festivals.
-
E.
Zerbst
Zerbst is a historic town in Saxony-Anhalt, Germany, known as the birthplace of Catherine the Great and for its former role as a princely residence.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8347a248190837e8c26f25f553a |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f12fa07fc081909a42f9c19ad38511 |
completed | April 28, 2026, 10:07 p.m. |
Created at: April 8, 2026, 9:28 p.m.