Triple
T10289567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eschwege |
E241325
|
entity |
| Predicate | river |
P165
|
FINISHED |
| Object | Werra |
E112665
|
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: Werra | Statement: [Eschwege, river, Werra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Werra Context triple: [Eschwege, river, Werra]
-
A.
Werra
chosen
The Werra is a major river in central Germany that forms one of the two headstreams of the Weser.
-
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.
Regnitz
The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
-
D.
Neckar
The Neckar is a significant river in southwestern Germany that flows through cities like Stuttgart and Heidelberg before joining the Rhine.
-
E.
Wupper
The Wupper is a river in North Rhine-Westphalia, Germany, known for flowing through the industrial city of Wuppertal and its surrounding region.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2d192288190a64c27a4f26b71fc |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e6afdf0c8190924cb14512a89ee8 |
completed | April 18, 2026, 8:16 p.m. |
Created at: April 6, 2026, 11:41 a.m.