Triple
T9876226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masaryk University |
E240079
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Brno |
E47149
|
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: Brno | Statement: [Masaryk University, locatedIn, Brno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brno Context triple: [Masaryk University, locatedIn, Brno]
-
A.
Brno
chosen
Brno is the second-largest city in the Czech Republic, known as a major cultural, educational, and industrial center in the historical region of Moravia.
-
B.
Kolín
Kolín is a historic industrial town and important transport hub on the Elbe River in the Central Bohemian Region of the Czech Republic.
-
C.
Ostrava
Ostrava is a major industrial and cultural city in the northeastern Czech Republic, near the borders with Poland and Slovakia.
-
D.
Olomouc
Olomouc is a historic city in the eastern Czech Republic known for its well-preserved old town, Baroque architecture, and UNESCO-listed Holy Trinity Column.
-
E.
Plzeň
Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
- 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3fb58d481908407898912c4b4e9 |
completed | April 2, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23d09790c8190be161d2dbef2e881 |
completed | April 5, 2026, 10:44 a.m. |
Created at: March 30, 2026, 8:37 p.m.