Triple
T4620463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sömmerda |
E100965
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Unstrut |
E263342
|
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: Unstrut | Statement: [Sömmerda, hasRiver, Unstrut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unstrut Context triple: [Sömmerda, hasRiver, Unstrut]
-
A.
Unstrut River
chosen
The Unstrut River is a tributary of the Saale in central Germany, flowing through Thuringia and Saxony-Anhalt and known for its scenic valleys, vineyards, and historic towns.
-
B.
Jagst
The Jagst is a river in Baden-Württemberg, Germany, known as one of the major right-bank tributaries of the Neckar and flowing through a largely rural, scenic landscape.
-
C.
Saale
The Saale is a major river in central Germany that flows through the states of Thuringia, Saxony-Anhalt, and Bavaria before joining the Elbe.
-
D.
Peene River
The Peene River is a lowland river in northeastern Germany, often called the "Amazon of the North" for its largely untouched wetlands and rich biodiversity.
-
E.
Wakenitz
Wakenitz is a river in northern Germany that flows through the city of Lübeck and connects the Ratzeburger See to the Trave River.
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59e560f481908abb1a97b4ff5795 |
completed | March 20, 2026, 2:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf410bd6b08190a0ad4af6e5f4b0b8 |
completed | March 22, 2026, 1:08 a.m. |
Created at: March 20, 2026, 1:12 p.m.