Triple

T1500939
Position Surface form Disambiguated ID Type / Status
Subject District of Galicia E29793 entity
Predicate containsCity P294 FINISHED
Object Ternopil E142410 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: Ternopil | Statement: [District of Galicia, containsCity, Ternopil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ternopil
Context triple: [District of Galicia, containsCity, Ternopil]
  • A. Ternopil chosen
    Ternopil is a city in western Ukraine known as a regional cultural and economic center with a historic old town and a picturesque lakeside setting.
  • B. Ivano-Frankivsk
    Ivano-Frankivsk is a historic city in western Ukraine known as a cultural, economic, and administrative center of the Carpathian region.
  • C. Zhytomyr
    Zhytomyr is a historic city in northwestern Ukraine known as an important regional center and the birthplace of pioneering rocket engineer Sergei Korolev.
  • D. Lutsk
    Lutsk is a historic city in northwestern Ukraine, known as the administrative center of Volyn Oblast and one of the region’s oldest cultural and economic hubs.
  • E. Chernihiv
    Chernihiv is a historic city in northern Ukraine known for its ancient churches, rich cultural heritage, and role as a regional administrative and memorial 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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c716941c819080596b00e29999c7 completed March 1, 2026, 11:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad40136c448190836426aa203590a8 completed March 8, 2026, 9:23 a.m.
Created at: March 1, 2026, 8:12 p.m.