Triple

T21385648
Position Surface form Disambiguated ID Type / Status
Subject Aalst E527486 entity
Predicate twinTown P1072 FINISHED
Object Gabrovo NE NERFINISHED

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: Gabrovo | Statement: [Aalst, twinTown, Gabrovo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gabrovo
Context triple: [Aalst, twinTown, Gabrovo]
  • A. Gabrovo chosen
    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.
  • B. Botevgrad
    Botevgrad is a town in western Bulgaria named in honor of the national revolutionary and poet Hristo Botev.
  • C. Targovishte
    Targovishte is a town in northeastern Bulgaria known as an administrative and economic center with historical roots dating back to the Ottoman period.
  • D. Sliven
    Sliven is a city in eastern Bulgaria known for its textile industry, historic role in Bulgarian national revival, and location near the eastern Balkan Mountains.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51f363c8190944000ab5523b02b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee62c9494081909efa74e189454dc6 completed April 26, 2026, 7:08 p.m.
Created at: April 16, 2026, 5:12 p.m.