Triple

T14247372
Position Surface form Disambiguated ID Type / Status
Subject Vörösmarty tér station E353169 entity
Predicate locatedUnder P10157 FINISHED
Object Vörösmarty tér E354800 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: Vörösmarty tér | Statement: [Vörösmarty tér station, locatedUnder, Vörösmarty tér]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vörösmarty tér
Context triple: [Vörösmarty tér station, locatedUnder, Vörösmarty tér]
  • A. 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.
  • B. Nagyvárad tér
    Nagyvárad tér is a metro station in Budapest that serves the city’s public transportation network on one of its main lines.
  • C. Széchenyi István tér
    Széchenyi István tér is a prominent square in central Budapest, Hungary, known for its grand riverside location by the Danube and its surrounding historic and cultural landmarks.
  • D. Szabadság tér
    Szabadság tér is a prominent public square in central Budapest known for its grand architecture, historical monuments, and political symbolism.
  • E. Vörösmarty Square chosen
    Vörösmarty Square is a prominent central plaza in Budapest known for its historic architecture, bustling cafés, and role as a major cultural and commercial hub.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de629464f88190817b190731bab156 completed April 14, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb73334c8190a96a92d199c3b101 completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:08 a.m.