Triple
T3866196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Czech lands |
E91859
|
entity |
| Predicate | containsMajorCity |
P316
|
FINISHED |
| Object | Plzeň |
E19529
|
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: Plzeň | Statement: [Czech lands, containsMajorCity, Plzeň]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Plzeň Context triple: [Czech lands, containsMajorCity, Plzeň]
-
A.
Plzeň
chosen
Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
-
B.
Pardubice
Pardubice is a city in the Czech Republic known for its ice hockey tradition, historic center, and as the hometown of legendary NHL goaltender Dominik Hašek.
-
C.
Liberec
Liberec is a city in the northern Czech Republic known for its textile industry heritage, mountainous surroundings, and the landmark Ještěd Tower.
-
D.
Jihlava
Jihlava is a historic city in the Czech Republic, known as one of the country’s oldest mining towns and a regional cultural and administrative center.
-
E.
Opava
Opava is a historic city in the Czech Republic’s Silesian region, known as a former political and cultural center of Silesia.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec3b8d988190b56d42ac1521e19c |
completed | March 9, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b562821c3c81909805cb877288405b |
completed | March 14, 2026, 1:28 p.m. |
Created at: March 9, 2026, 3:19 p.m.