Triple
T4297101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brno region |
E99740
|
entity |
| Predicate | containsRiver |
P165
|
FINISHED |
| Object | Svitava |
E240078
|
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: Svitava | Statement: [Brno region, containsRiver, Svitava]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Svitava Context triple: [Brno region, containsRiver, Svitava]
-
A.
Svitava
chosen
Svitava is a river in the Czech Republic that flows through the city of Brno and is one of its main waterways.
-
B.
Zemplín
Zemplín is a historical and geographical region in eastern Slovakia known for its wine production, cultural heritage, and proximity to the borders with Hungary and Ukraine.
-
C.
Berounka
Berounka is a major river in western Bohemia in the Czech Republic, known for flowing through the Plzeň Region and eventually joining the Vltava near Prague.
-
D.
Vávrová
Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
-
E.
Rožňava
Rožňava is a historic mining town in southern Slovakia known for its well-preserved medieval center and proximity to the Slovak Karst region.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3509aebd48190af38f2e37f07869a |
completed | March 12, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d073936c8190b48045f8370ea27f |
completed | March 14, 2026, 9:17 p.m. |
Created at: March 12, 2026, 11:08 p.m.