Triple
T11133309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unstrut |
E263342
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Wipper |
E748790
|
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: Wipper | Statement: [Unstrut, hasTributary, Wipper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wipper Context triple: [Unstrut, hasTributary, Wipper]
-
A.
Wipper
chosen
The Wipper is a river in central Germany that flows through the Kyffhäuserkreis district and ultimately feeds into the Unstrut.
-
B.
Welper
Welper is a district of the town of Hattingen in North Rhine-Westphalia, Germany.
-
C.
Weener
Weener is a small town and municipality in the Leer district of Lower Saxony in northwestern Germany, known for its historic harbor and location on the River Ems.
-
D.
Weyer
Weyer is a village and district within the town of Mechernich in the Euskirchen district of North Rhine-Westphalia, Germany.
-
E.
Wiske
Wiske is a small river in North Yorkshire, England, known as one of the tributaries feeding into the River Swale.
- 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_69e441f00d7c8190a8fe8e0c1169e6b0 |
completed | April 19, 2026, 2:46 a.m. |
Created at: April 8, 2026, 9:28 p.m.