Triple

T3528742
Position Surface form Disambiguated ID Type / Status
Subject Hildesheim E74604 entity
Predicate hasTwinTown P919 FINISHED
Object Gelendzhik E166972 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: Gelendzhik | Statement: [Hildesheim, hasTwinTown, Gelendzhik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gelendzhik
Context triple: [Hildesheim, hasTwinTown, Gelendzhik]
  • A. Gelendzhik chosen
    Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
  • B. Novorossiysk
    Novorossiysk is a major port city on Russia’s Black Sea coast that serves as an important naval and commercial hub.
  • C. Yevpatoria
    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.
  • D. Taganrog
    Taganrog is a port city in southwestern Russia on the northern coast of the Sea of Azov, known for its maritime trade and as the birthplace of writer Anton Chekhov.
  • E. Berdyansk
    Berdyansk is a port city in southeastern Ukraine on the northern coast of the Sea of Azov, known for its maritime trade, beaches, and resort facilities.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc6e9188819093480b39f263ce75 completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f018fe0481908291195f55fd765f completed March 14, 2026, 5:20 a.m.
Created at: March 8, 2026, 3:19 p.m.