Triple
T14368026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Budapest Metro Line 2 |
E356284
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Blaha Lujza tér
Blaha Lujza tér is a major square and busy public transport hub in central Budapest, Hungary.
|
E1096314
|
NE FINISHED |
How this triple was built (4 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 | Statement: [Budapest Metro Line 2, hasStation, Blaha Lujza tér]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blaha Lujza tér Context triple: [Budapest Metro Line 2, hasStation, Blaha Lujza tér]
-
A.
Parádfürdő
Parádfürdő is a spa village in northern Hungary known for its mineral springs and scenic location within the Mátra mountain region.
-
B.
Rákóczi tér
Rákóczi tér is a public square and transport hub in Budapest known for its central location and metro station in the Józsefváros district.
-
C.
Bajza utca
Bajza utca is a Budapest Metro station on the historic M1 (Millennium Underground) line in Hungary.
-
D.
Népliget area
The Népliget area is a large public park and transport hub in Budapest, Hungary, known for its green spaces, sports facilities, and major international bus station.
-
E.
Belá
Belá is a mountain river in northern Slovakia known for its clear waters, dynamic flow, and popularity among whitewater enthusiasts.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Blaha Lujza tér Triple: [Budapest Metro Line 2, hasStation, Blaha Lujza tér]
Generated description
Blaha Lujza tér is a major square and busy public transport hub in central Budapest, Hungary.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Blaha Lujza tér Target entity description: Blaha Lujza tér is a major square and busy public transport hub in central Budapest, Hungary.
-
A.
Parádfürdő
Parádfürdő is a spa village in northern Hungary known for its mineral springs and scenic location within the Mátra mountain region.
-
B.
Rákóczi tér
Rákóczi tér is a public square and transport hub in Budapest known for its central location and metro station in the Józsefváros district.
-
C.
Bajza utca
Bajza utca is a Budapest Metro station on the historic M1 (Millennium Underground) line in Hungary.
-
D.
Népliget area
The Népliget area is a large public park and transport hub in Budapest, Hungary, known for its green spaces, sports facilities, and major international bus station.
-
E.
Belá
Belá is a mountain river in northern Slovakia known for its clear waters, dynamic flow, and popularity among whitewater enthusiasts.
- F. None of above. chosen
Provenance (5 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8faf00e8819087d7100e9d8c1877 |
completed | April 14, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c51bf888190b1776461884c4514 |
completed | May 8, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fd5020e6f081909686fe3d143d31fa |
completed | May 8, 2026, 2:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd50c2cdb48190a438dc0641e3c25e |
completed | May 8, 2026, 2:56 a.m. |
Created at: April 10, 2026, 1:15 a.m.