Triple
T9162932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olomouc Region |
E219870
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Přerov |
E584545
|
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: Přerov | Statement: [Olomouc Region, hasMajorCity, Přerov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Přerov Context triple: [Olomouc Region, hasMajorCity, Přerov]
-
A.
Přerov
chosen
Přerov is a city in the Olomouc Region of the Czech Republic, known as an important industrial and transport hub on the Bečva River.
-
B.
Vsetín
Vsetín is a town in the eastern Czech Republic known as an industrial and cultural center of the Moravian Wallachia region.
-
C.
Bražec
Bražec is a small village and administrative part of the town of Náchod in the Hradec Králové Region of the Czech Republic.
-
D.
Říčany
Říčany is a town in the Czech Republic, located just southeast of Prague and known as a popular residential and commuter suburb with historical roots.
-
E.
Prostějov
Prostějov is a historic city in the Olomouc Region of the Czech Republic known for its long-standing textile industry and Central European cultural 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_69ca83e3633c81908688a9fa2306ba99 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaa2d6628819084ac4734650fe912 |
completed | April 1, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d5c75980e4819080f486b454f211a2 |
completed | April 8, 2026, 3:11 a.m. |
Created at: March 30, 2026, 7:21 p.m.