Triple

T7238571
Position Surface form Disambiguated ID Type / Status
Subject Blagnac E155294 entity
Predicate hasTwinTown P919 FINISHED
Object Targovishte E575939 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: Targovishte | Statement: [Blagnac, hasTwinTown, Targovishte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Targovishte
Context triple: [Blagnac, hasTwinTown, Targovishte]
  • A. Targovishte chosen
    Targovishte is a town in northeastern Bulgaria known as an administrative and economic center with historical roots dating back to the Ottoman period.
  • B. Asenovgrad
    Asenovgrad is a town in southern Bulgaria known as a gateway to the Rhodope Mountains and a regional center rich in historical and religious landmarks.
  • C. Shumen
    Shumen is a city in northeastern Bulgaria known for its historical significance, including nearby medieval capitals and the Monument to 1300 Years of Bulgaria.
  • D. Tarnovo
    Tarnovo, often called Veliko Tarnovo, is a historic Bulgarian city famed as a medieval capital and cultural stronghold, known for its dramatic hillside setting and well-preserved architectural heritage.
  • E. Gabrovo
    Gabrovo is a town in central Bulgaria known for its humor and satire traditions, as well as its historical role in the country’s industrial development.
  • 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_69c688143bfc81908d4176617735e601 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea368fb88190bd9e991e8b94dac6 completed March 27, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db0fd90881908c6b84f1292f0b01 completed March 28, 2026, 1:43 p.m.
Created at: March 27, 2026, 2:55 p.m.