Triple

T5074475
Position Surface form Disambiguated ID Type / Status
Subject Maribor E114358 entity
Predicate hasTwinTown P919 FINISHED
Object Pécs, Hungary E38480 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: Pécs, Hungary | Statement: [Maribor, hasTwinTown, Pécs, Hungary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pécs, Hungary
Context triple: [Maribor, hasTwinTown, Pécs, Hungary]
  • A. Pécs chosen
    Pécs is a historic cultural and university city in southwestern Hungary, renowned for its Roman and Ottoman heritage and its designation as a European Capital of Culture in 2010.
  • B. Kaposvár, Hungary
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • C. Budaörs, Hungary
    Budaörs is a suburban town just west of Budapest in Hungary, known for its rapid post-communist development, commercial centers, and role as a key transport hub near the capital.
  • D. Ricse, Hungary
    Ricse, Hungary is a small village in northeastern Hungary best known as the birthplace of film mogul Adolph Zukor, a founder of Paramount Pictures.
  • E. Siófok
    Siófok is a popular resort town on the southern shore of Lake Balaton in Hungary, known for its beaches and vibrant summer 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_69bd443cf28c8190ad371d603563dbdd completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd74d0be1c819081b26235fe602a30 completed March 20, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba689ee081909a6bb75c6da07db5 completed March 21, 2026, 3:34 p.m.
Created at: March 20, 2026, 1:39 p.m.