Triple

T17900920
Position Surface form Disambiguated ID Type / Status
Subject Tsaritsa Irina E447573 entity
Predicate associatedWith P37 FINISHED
Object Sofia region 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: Sofia region | Statement: [Tsaritsa Irina, associatedWith, Sofia region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sofia region
Context triple: [Tsaritsa Irina, associatedWith, Sofia region]
  • A. Sofia Region
    Sofia Region is an administrative region in northern Madagascar known for its mountainous landscapes, including the country’s highest peak, Maromokotro.
  • B. Sofia Province chosen
    Sofia Province is an administrative region in western Bulgaria that surrounds, but does not include, the national capital city of Sofia.
  • C. Sofia City Province
    Sofia City Province is the administrative region encompassing Bulgaria’s capital, Sofia, serving as the country’s political, economic, and cultural center.
  • D. Sredets region
    Sredets region is a historical area in western Bulgaria traditionally associated with the medieval city of Sredets, later known as Sofia.
  • E. Sliven Province
    Sliven Province is an administrative region in southeastern Bulgaria known for its mountainous landscapes, wine production, and the city of Sliven as its administrative center.
  • 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_69d8b9f59bd48190a6fc925a855b8bac completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49d8321bc8190a3f679d96323cbbb completed April 19, 2026, 9:16 a.m.
Created at: April 10, 2026, 10:19 a.m.