Triple

T13111495
Position Surface form Disambiguated ID Type / Status
Subject Velenje E310981 entity
Predicate hasTwinTown P919 FINISHED
Object Valjevo E516202 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: Valjevo | Statement: [Velenje, hasTwinTown, Valjevo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valjevo
Context triple: [Velenje, hasTwinTown, Valjevo]
  • A. Valjevo chosen
    Valjevo is a historic city in western Serbia known for its role in World War I and its position as a regional cultural and economic center.
  • B. Zrenjanin
    Zrenjanin is a city in northern Serbia known as an economic, cultural, and administrative center of the Banat region.
  • C. Vinkovci
    Vinkovci is a historic town in eastern Croatia, recognized as one of the oldest continuously inhabited settlements in Europe and a key urban center of the Slavonia region.
  • D. Barajevo
    Barajevo is a suburban municipality of Belgrade, Serbia, located in the southern part of the city’s administrative area.
  • E. Zemun
    Zemun is a historic urban municipality of Belgrade, Serbia, known for its preserved old town, Danube riverfront, and distinctive Central European architectural heritage.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817e4f408190b77c198b4157d77a completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5d205408190883b67739d5efaa7 completed May 3, 2026, 7:14 a.m.
Created at: April 9, 2026, 9:05 p.m.