Triple

T1752730
Position Surface form Disambiguated ID Type / Status
Subject Pécs E38480 entity
Predicate twinCity P1072 FINISHED
Object Eszék (Osijek) E133925 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: Eszék (Osijek) | Statement: [Pécs, twinCity, Eszék (Osijek)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eszék (Osijek)
Context triple: [Pécs, twinCity, Eszék (Osijek)]
  • A. Osijek chosen
    Osijek is a prominent city in eastern Croatia known as an economic, cultural, and educational center of the Slavonia region.
  • B. Barajevo
    Barajevo is a suburban municipality of Belgrade, Serbia, located in the southern part of the city’s administrative area.
  • C. Zrenjanin
    Zrenjanin is a city in northern Serbia known as an economic, cultural, and administrative center of the Banat region.
  • D. Gornji Grad
    Gornji Grad is the historic upper town of Zagreb, known for its medieval streets, landmarks like St. Mark’s Church and the Stone Gate, and its role as the city’s political and cultural center.
  • E. Stari Grad
    Stari Grad is the historic central municipality of Belgrade, known for its old town architecture, cultural landmarks, and key administrative and commercial areas.
  • 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_69a8862bdb2081908aefe831c8aa8017 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa641432d88190ab4254cb4c3ad402 completed March 6, 2026, 5:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0e625c48190a0fbda31010bdc5f completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:31 p.m.