Triple
T14866722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Városliget |
E349632
|
entity |
| Predicate | publicTransportStop |
P6657
|
FINISHED |
| Object | Széchenyi fürdő station |
E70148
|
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: Széchenyi fürdő station | Statement: [Városliget, publicTransportStop, Széchenyi fürdő station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Széchenyi fürdő station Context triple: [Városliget, publicTransportStop, Széchenyi fürdő station]
-
A.
Széchenyi Thermal Bath
chosen
Széchenyi Thermal Bath is one of Europe’s largest and most famous medicinal bath complexes, renowned for its neo-baroque architecture and extensive thermal pools in Budapest, Hungary.
-
B.
Lehel station
Lehel station is a Munich U-Bahn underground railway station serving the Altstadt-Lehel district of Munich, Germany.
-
C.
Gellért Thermal Bath
Gellért Thermal Bath is a historic Art Nouveau spa complex in Budapest renowned for its thermal pools, ornate architecture, and traditional Hungarian bathing culture.
-
D.
Kaposvár railway station
Kaposvár railway station is the main rail transport hub serving the city of Kaposvár in southwestern Hungary.
-
E.
Hévíz
Hévíz is a Hungarian spa town famous for its large natural thermal lake and wellness tourism.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5761c688190b4477cb081554b51 |
completed | April 15, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe651067cc8190b9c218ef1f802762 |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:55 a.m.