Triple

T10183847
Position Surface form Disambiguated ID Type / Status
Subject Port of Chornomorsk E236857 entity
Predicate servesCity P82 FINISHED
Object Odesa 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: Odesa | Statement: [Port of Chornomorsk, servesCity, Odesa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Odesa
Context triple: [Port of Chornomorsk, servesCity, Odesa]
  • 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. Odessa
    Odessa is a mid-sized city in western Texas known for its oil industry, high school football culture, and role in the Permian Basin energy region.
  • C. Odessa
    Odessa is a central, devoutly religious housekeeper in James Baldwin’s play "The Amen Corner," known for her loyalty and moral grounding amid the story’s family and church conflicts.
  • D. Mykolaiv
    Mykolaiv is a major shipbuilding and industrial city in southern Ukraine located near the Black Sea.
  • E. 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.
  • 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_69ca84d7260c8190bfbec36762943f37 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cded3566f881909e0d1366f501d554 completed April 2, 2026, 4:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69d96b0e4eac8190af28db3d334852cb completed April 10, 2026, 9:26 p.m.
Created at: March 30, 2026, 9:12 p.m.