Triple

T14863973
Position Surface form Disambiguated ID Type / Status
Subject Karakays E349570 entity
Predicate region P40 FINISHED
Object Yevpatoria E73725 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: Yevpatoria | Statement: [Karakays, region, Yevpatoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yevpatoria
Context triple: [Karakays, region, Yevpatoria]
  • A. Yevpatoria chosen
    Yevpatoria is a historic resort and port city on the western coast of Crimea, known for its beaches, therapeutic mud treatments, and diverse cultural heritage.
  • B. Feodosia
    Feodosia is a historic port city on the southeastern coast of Crimea, known for its Black Sea beaches, medieval fortifications, and association with painter Ivan Aivazovsky.
  • C. Sevastopol
    Sevastopol is a major port city on the Black Sea, historically significant as a naval base and the site of key military conflicts.
  • D. Simferopol
    Simferopol is the administrative and cultural center of Crimea, known as a key regional hub for transportation, education, and industry.
  • E. Gelendzhik
    Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded574d0ec8190a6afed672ba6c2f9 completed April 15, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9687a5888190a6e6ffd781f64edc completed May 9, 2026, 2:05 a.m.
Created at: April 10, 2026, 1:54 a.m.