Triple
T12854577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Łužica |
E307414
|
entity |
| Predicate | hasMajorRiver |
P165
|
FINISHED |
| Object | Lusatian Neisse |
E246387
|
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: Lusatian Neisse | Statement: [Łužica, hasMajorRiver, Lusatian Neisse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lusatian Neisse Context triple: [Łužica, hasMajorRiver, Lusatian Neisse]
-
A.
Lusatian Neisse
chosen
The Lusatian Neisse is a river in Central Europe that flows through the Czech Republic, Germany, and Poland, forming part of the German–Polish border.
-
B.
Geringswalde
Geringswalde is a small town in the Free State of Saxony in eastern Germany, known for its rural character and location within the Central Saxon region.
-
C.
Riedenburg
Riedenburg is a small Bavarian town in southern Germany known for its scenic location in the Altmühl Valley and its historic castles.
-
D.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
-
E.
Schwedt
Schwedt is a town in northeastern Germany, located on the Oder River near the Polish border, known for its industrial facilities and cross-border regional ties.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97021df7481909cd42a0f72040aa5 |
completed | April 10, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd9495b9748190905b02621939b326 |
completed | May 8, 2026, 7:45 a.m. |
Created at: April 9, 2026, 5:37 p.m.