Triple

T2586506
Position Surface form Disambiguated ID Type / Status
Subject Amiens E58016 entity
Predicate twinnedWith P1072 FINISHED
Object Odessa E38290 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: Odessa | Statement: [Amiens, twinnedWith, Odessa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Odessa
Context triple: [Amiens, twinnedWith, Odessa]
  • A. Odesa chosen
    Odesa is a major port city on the Black Sea in southern Ukraine, known for its historic architecture, multicultural heritage, and key economic and cultural role in the country.
  • B. 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.
  • C. Kryvyi Rih
    Kryvyi Rih is a major industrial city in central Ukraine known for its extensive iron ore mining and steel production.
  • D. Mykolaiv
    Mykolaiv is a major shipbuilding and industrial city in southern Ukraine located near the Black Sea.
  • 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_69ab4ac019c8819094add11c46706e32 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd3f6f6ac8190abff7b8b6ff3c023 completed March 7, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69b28db1ddec8190a6d346afc79cfd8e completed March 12, 2026, 9:56 a.m.
Created at: March 6, 2026, 9:49 p.m.