Triple

T14224542
Position Surface form Disambiguated ID Type / Status
Subject Kazinczy Street Synagogue E352583 entity
Predicate namedAfter P63 FINISHED
Object Kazinczy Street E364082 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: Kazinczy Street | Statement: [Kazinczy Street Synagogue, namedAfter, Kazinczy Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kazinczy Street
Context triple: [Kazinczy Street Synagogue, namedAfter, Kazinczy Street]
  • A. Kazinczy Street chosen
    Kazinczy Street is a popular street in Budapest known for its vibrant nightlife, ruin pubs, and cultural venues.
  • B. Kossuth Lajos Street
    Kossuth Lajos Street is a central thoroughfare in Budapest’s historic Pest side, known for its heavy traffic, shops, and proximity to major downtown landmarks.
  • C. Andrássy Avenue
    Andrássy Avenue is a grand, historic boulevard in Budapest renowned for its elegant architecture, cultural institutions, and status as a UNESCO World Heritage Site.
  • D. Szent György Street
    Szent György Street is a historic street in Budapest’s Castle District, known for its proximity to key landmarks and its role in the city’s medieval urban layout.
  • E. Váci Street
    Váci Street is one of Budapest’s main pedestrian shopping streets, known for its historic architecture, boutiques, cafés, and tourist-oriented atmosphere in the city center.
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6227c288819081473ce44f9f0934 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd949df6688190ac92f7e0945bce02 completed May 8, 2026, 7:45 a.m.
Created at: April 10, 2026, 1:06 a.m.