Triple

T20222421
Position Surface form Disambiguated ID Type / Status
Subject Skadovsk Port E495288 entity
Predicate nearbyCity P350 FINISHED
Object Skadovsk NE NERFINISHED

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: Skadovsk | Statement: [Skadovsk Port, nearbyCity, Skadovsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skadovsk
Context triple: [Skadovsk Port, nearbyCity, Skadovsk]
  • A. Skadovsk chosen
    Skadovsk is a port city in southern Ukraine on the Black Sea coast, known for its maritime trade and seaside tourism.
  • B. Metelkova City
    Metelkova City is an autonomous cultural and social center in Ljubljana, Slovenia, known for its alternative art scene, vibrant nightlife, and politically engaged community.
  • C. Proskurov
    Proskurov is the former name of the Ukrainian city now known as Khmelnytskyi, a regional center in western Ukraine.
  • D. Shpola
    Shpola is a small town in central Ukraine that serves as an administrative center within Cherkasy Oblast.
  • E. Černilov
    Černilov is a municipality and village in the Hradec Králové Region of the Czech Republic, known for its rural character and proximity to the city of Hradec Králové.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626cff80819097b530718a7c98b6 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66fd729548190942bcf842f03c4cd completed April 20, 2026, 6:26 p.m.
Created at: April 11, 2026, 11:39 p.m.