Triple

T16886732
Position Surface form Disambiguated ID Type / Status
Subject Teesside E421558 entity
Predicate hasPart P35 FINISHED
Object Eston E738302 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: Eston | Statement: [Teesside, hasPart, Eston]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eston
Context triple: [Teesside, hasPart, Eston]
  • A. Eston chosen
    Eston is a town in North Yorkshire, England, historically associated with ironstone mining and now part of the borough of Redcar and Cleveland.
  • B. Estonia
    Estonia is a Northern European country on the Baltic Sea known for its advanced digital society, rapid post-Soviet economic development, and membership in organizations such as the European Union and NATO.
  • C. Tartumaa
    Tartumaa is a historical region in southeastern Estonia centered around the city of Tartu, known for its cultural and educational significance.
  • D. Laietania
    Laietania was an ancient Iberian region along the northeastern coast of the Iberian Peninsula, roughly corresponding to part of modern Catalonia around present-day Barcelona.
  • E. Suvalkija
    Suvalkija is one of the ethnographic regions of Lithuania, known for its distinct cultural traditions, dialect, and historical development in the southwestern 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_69d889d470fc8190b4aec199636c0c56 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc126e881909dae8133ad34acc9 completed April 18, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d45647f481908ae76a0b8fe8a9cb completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:29 a.m.