Triple
T15551455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Budapest tram network |
E370752
|
entity |
| Predicate | hasStop |
P17789
|
FINISHED |
| Object | Blaha Lujza tér stop |
E1096314
|
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: Blaha Lujza tér stop | Statement: [Budapest tram network, hasStop, Blaha Lujza tér stop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blaha Lujza tér stop Context triple: [Budapest tram network, hasStop, Blaha Lujza tér stop]
-
A.
Blaha Lujza tér
chosen
Blaha Lujza tér is a major square and busy public transport hub in central Budapest, Hungary.
-
B.
Lujza
Lujza is a given name, primarily used in Central and Eastern Europe, that corresponds to the name Luisa or Louise in other languages.
-
C.
Vigadó tér
Vigadó tér is a prominent square on the Pest side of central Budapest, known for its riverside location along the Danube and its proximity to major cultural and historic landmarks.
-
D.
Zastávka
Zastávka is a local administrative part of the town of Přeštice in the Plzeň Region of the Czech Republic.
-
E.
Lehel tér
Lehel tér is a major square and transport hub in Budapest, known for its busy metro station, market hall, and commercial activity.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04a9551288190a583e8291c35f521 |
completed | April 16, 2026, 2:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4560008c81908ebd278c3dc45045 |
completed | May 9, 2026, 2:32 p.m. |
Created at: April 10, 2026, 4:08 a.m.