Triple
T3010281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German-Czech border |
E82198
|
entity |
| Predicate | hasMajorBorderRiver |
P165
|
FINISHED |
| Object | 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: Neisse | Statement: [German-Czech border, hasMajorBorderRiver, Neisse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neisse Context triple: [German-Czech border, hasMajorBorderRiver, Neisse]
-
A.
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.
-
B.
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.
-
C.
Riesa
Riesa is a town in the German state of Saxony, situated on the Elbe River and known historically as an important regional railway and industrial center.
-
D.
Schkopau
Schkopau is a municipality in the Saalekreis district of Saxony-Anhalt, Germany, known for its large chemical industry complex.
-
E.
Prenzlau
Prenzlau is a historic town in northeastern Germany’s Brandenburg region, known for its medieval architecture and role as a regional administrative center.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9e11c4188190a3ae8fd0cbd8c2c0 |
completed | March 8, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4dae657ec81909e8a99e4ccd95bfc |
completed | March 14, 2026, 3:49 a.m. |
Created at: March 8, 2026, 3 p.m.