Triple
T810867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middle Franconia |
E17540
|
entity |
| Predicate | hasMajorRiver |
P165
|
FINISHED |
| Object | Rednitz |
E19589
|
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: Rednitz | Statement: [Middle Franconia, hasMajorRiver, Rednitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rednitz Context triple: [Middle Franconia, hasMajorRiver, Rednitz]
-
A.
Rednitz
chosen
The Rednitz is a river in Bavaria, Germany, that flows through cities such as Fürth and joins with the Pegnitz to form the Regnitz.
-
B.
Nischel
Nischel is the local colloquial nickname for the large Karl Marx Monument in Chemnitz, Germany.
-
C.
Baumwerder
Baumwerder is a small island located in Tegeler See, a lake in the Berlin district of Reinickendorf, Germany.
-
D.
Kritzinger
Kritzinger is a German surname most notably associated with Friedrich Wilhelm Kritzinger, a high-ranking Nazi official involved in the administrative planning of the Holocaust.
-
E.
Veluws
Veluws is a Dutch Low Saxon dialect spoken in the Veluwe region of the Netherlands, closely related to other eastern Dutch dialects such as Achterhooks.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab282fe48190a05ee97550843cd7 |
completed | March 1, 2026, 9:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a826cc938481909e420185871a5d27 |
completed | March 4, 2026, 12:34 p.m. |
Created at: March 1, 2026, 7:38 p.m.