Triple
T15160476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D5 motorway |
E362198
|
entity |
| Predicate | passesThrough |
P225
|
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: [D5 motorway, passesThrough, Plzeň]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Plzeň Context triple: [D5 motorway, passesThrough, 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.
Žatec
Žatec is a historic Czech town in the Ústí nad Labem Region renowned for its long-standing hop-growing tradition and beer production.
-
E.
Jihlava
Jihlava is a river in the Czech Republic that flows through the historical region of Moravia, including the city of Jihlava, before joining the Svratka River.
- 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_69d85a087b7c81908baa94a53dac8d68 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060f2efc8190aa0eb5fb8d4ce085 |
completed | April 15, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed32637748190b566602b5b37fbd3 |
completed | May 9, 2026, 6:24 a.m. |
Created at: April 10, 2026, 3:08 a.m.