Triple
T3751753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Würschnitz |
E81346
|
entity |
| Predicate | hasMouthIn |
P1008
|
FINISHED |
| Object | Chemnitz (river) |
E14568
|
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: Chemnitz (river) | Statement: [Würschnitz, hasMouthIn, Chemnitz (river)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chemnitz (river) Context triple: [Würschnitz, hasMouthIn, Chemnitz (river)]
-
A.
Chemnitz River
chosen
The Chemnitz River is a waterway in the German state of Saxony that flows through and gives its name to the city of Chemnitz.
-
B.
Würschnitz
Würschnitz is a small river in Saxony, Germany, that serves as one of the tributaries feeding into the Chemnitz River.
-
C.
Orlice River
The Orlice River is a significant river in the Czech Republic that flows through eastern Bohemia and joins the Elbe near the city of Hradec Králové.
-
D.
Wakenitz
Wakenitz is a river in northern Germany that flows through the city of Lübeck and connects the Ratzeburger See to the Trave River.
-
E.
Rüdnitz
Rüdnitz is a small municipality in the Barnim district of the federal state of Brandenburg in northeastern Germany.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb909bb4819088559f90d718f72f |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fb0c116c8190a74fff15a5de8296 |
completed | March 14, 2026, 6:07 a.m. |
Created at: March 8, 2026, 3:35 p.m.