Triple
T4797857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plzeň main railway station |
E106755
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Domažlice |
E295569
|
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: Domažlice | Statement: [Plzeň main railway station, connectsTo, Domažlice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Domažlice Context triple: [Plzeň main railway station, connectsTo, Domažlice]
-
A.
Domažlice
chosen
Domažlice is a historic town in the western Czech Republic known for its well-preserved medieval center and rich Chodové folk traditions.
-
B.
Jizbice
Jizbice is a small locality that forms part of the town of Náchod in the Hradec Králové Region of the Czech Republic.
-
C.
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.
-
D.
Ruzyně
Ruzyně is a district in the western part of Prague, Czech Republic, best known as the location of the city’s main international airport.
-
E.
Slaný
Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
- 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6632708c8190b627d99363ab062c |
completed | March 20, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be778861a88190bf7c9f04d903a5e2 |
completed | March 21, 2026, 10:48 a.m. |
Created at: March 20, 2026, 1:22 p.m.