Triple

T9223239
Position Surface form Disambiguated ID Type / Status
Subject Rishon LeZion E221613 entity
Predicate hasSisterCity P919 FINISHED
Object Debrecen, Hungary E37144 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: Debrecen, Hungary | Statement: [Rishon LeZion, hasSisterCity, Debrecen, Hungary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Debrecen, Hungary
Context triple: [Rishon LeZion, hasSisterCity, Debrecen, Hungary]
  • A. Debrecen chosen
    Debrecen is Hungary’s second-largest city and a key cultural, economic, and educational center in the country’s eastern region.
  • 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. Kisvárda, Hungary
    Kisvárda is a small town in northeastern Hungary known for its historic castle, thermal baths, and role as a regional cultural and economic center.
  • E. 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.
  • 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_69ca83ec8db08190a9110df8232885d2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda7903208190b4e29a1591aab78a completed April 1, 2026, 8:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0664565748190a45cf382fca72cbe completed April 4, 2026, 1:15 a.m.
Created at: March 30, 2026, 7:28 p.m.