Triple
T185221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baroque |
E3965
|
entity |
| Predicate | hasNotableCenter |
P6682
|
FINISHED |
| Object | Prague |
E14162
|
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: Prague | Statement: [Baroque, hasNotableCenter, Prague]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prague Context triple: [Baroque, hasNotableCenter, Prague]
-
A.
Prague
chosen
Prague is the historic capital city of the Czech Republic, renowned for its well-preserved medieval architecture, iconic Charles Bridge and Prague Castle, and vibrant cultural life.
-
B.
Plzeň
Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
-
C.
Hradec Králové
Hradec Králové is a historic city in the Czech Republic known for its educational institutions, modernist architecture, and role as a regional cultural and economic center.
-
D.
Bratislava
Bratislava is the capital and largest city of Slovakia, situated along the Danube River near the borders with Austria and Hungary.
-
E.
Vienna
Vienna is a suburban town in Fairfax County, Virginia, known for its residential neighborhoods, proximity to Washington, D.C., and access to the Washington Metro via the nearby Vienna/Fairfax–GMU station.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bc834388190a93ec1ab0d5946de |
completed | Feb. 28, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a362b97500819088c4f547f6ee38d4 |
completed | Feb. 28, 2026, 9:48 p.m. |
Created at: Feb. 28, 2026, 2:40 a.m.