Triple

T817691
Position Surface form Disambiguated ID Type / Status
Subject Sheffield E17685 entity
Predicate twinTown P1072 FINISHED
Object Donetsk
Donetsk is a major industrial city in eastern Ukraine, historically known for its coal mining and steel production.
 E110135 NE FINISHED

How this triple was built (4 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: [Sheffield, twinTown, Donetsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Donetsk
Context triple: [Sheffield, twinTown, Donetsk]
  • A. 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.
  • B. Kharkiv
    Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
  • C. Kryvyi Rih
    Kryvyi Rih is a major industrial city in central Ukraine known for its extensive iron ore mining and steel production.
  • D. Mariupol
    Mariupol is a major industrial city in southeastern Ukraine known for its strategic port on the Sea of Azov and its significant role in recent military conflicts.
  • E. Simferopol
    Simferopol is the administrative and cultural center of Crimea, known as a key regional hub for transportation, education, and industry.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Donetsk
Triple: [Sheffield, twinTown, Donetsk]
Generated description
Donetsk is a major industrial city in eastern Ukraine, historically known for its coal mining and steel production.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Donetsk
Target entity description: Donetsk is a major industrial city in eastern Ukraine, historically known for its coal mining and steel production.
  • A. 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.
  • B. Kharkiv
    Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
  • C. Kryvyi Rih
    Kryvyi Rih is a major industrial city in central Ukraine known for its extensive iron ore mining and steel production.
  • D. Mariupol
    Mariupol is a major industrial city in southeastern Ukraine known for its strategic port on the Sea of Azov and its significant role in recent military conflicts.
  • E. Simferopol
    Simferopol is the administrative and cultural center of Crimea, known as a key regional hub for transportation, education, and industry.
  • F. None of above. chosen

Provenance (5 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab63f4a48190a61a14c3c41ed641 completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7edfcb7a88190b3670c6ef2b93609 completed March 4, 2026, 8:31 a.m.
NEDg Description generation batch_69a7f72ae04c81908ede9a57670cd995 completed March 4, 2026, 9:11 a.m.
NED2 Entity disambiguation (via description) batch_69a7f7cf9310819090384bbd7f45ca38 completed March 4, 2026, 9:13 a.m.
Created at: March 1, 2026, 7:38 p.m.