Triple

T10249540
Position Surface form Disambiguated ID Type / Status
Subject European route E50 E240302 entity
Predicate passesThroughCity P416 FINISHED
Object Donetsk E110135 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: Donetsk | Statement: [European route E50, passesThroughCity, Donetsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Donetsk
Context triple: [European route E50, passesThroughCity, Donetsk]
  • A. Donetsk chosen
    Donetsk is a major industrial city in eastern Ukraine, historically known for its coal mining and steel production.
  • B. Zaporizhzhia
    Zaporizhzhia is a major industrial city in southeastern Ukraine, known for its large hydroelectric power plant on the Dnieper River and its significant role in the country’s energy and manufacturing sectors.
  • C. Donetsk Oblast
    Donetsk Oblast is an industrial and heavily urbanized region in eastern Ukraine, historically known for coal mining and metallurgy and currently a focal point of the Russo-Ukrainian conflict.
  • D. Kherson
    Kherson is a port city in southern Ukraine near the Black Sea, historically significant as a shipbuilding and industrial center and strategically important due to its location on the Dnieper River.
  • E. Dnipro
    Dnipro is one of Ukraine’s largest industrial and cultural centers, located on the Dnieper River in the central-eastern part of the country.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d23c4cd88190b99e65a074b68d6b completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69de54d83e44819097abf6714bd48680 completed April 14, 2026, 2:53 p.m.
Created at: April 6, 2026, 11:28 a.m.