Triple

T3917853
Position Surface form Disambiguated ID Type / Status
Subject Dimitrov Communist Youth Union E88886 entity
Predicate headquartersLocation P62 FINISHED
Object Sofia E31299 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: Sofia | Statement: [Dimitrov Communist Youth Union, headquartersLocation, Sofia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sofia
Context triple: [Dimitrov Communist Youth Union, headquartersLocation, Sofia]
  • A. Sofia chosen
    Sofia is the capital and largest city of Bulgaria, known as a major cultural, economic, and historical center in the Balkans.
  • B. Sofia
    Sofia is a strong-willed, outspoken woman in Alice Walker’s "The Color Purple," known for her resilience and defiance against oppression.
  • C. Sofia
    Sofia is a feminine given name of Greek origin, widely used in many cultures and commonly associated with the meaning "wisdom."
  • D. Sofya
    Sofya is the Russian given name of Sophia Tolstaya, the wife and muse of novelist Leo Tolstoy.
  • E. Plovdiv
    Plovdiv is Bulgaria’s second-largest city and one of Europe’s oldest continuously inhabited urban centers, known for its Roman amphitheater, Old Town, and rich cultural heritage.
  • 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_69aed955229881909e85e73ffab1d343 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed5797508190adaddb84575d9bb3 completed March 9, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55614ffa48190b15a1c2ec20638f2 completed March 14, 2026, 12:35 p.m.
Created at: March 9, 2026, 3:22 p.m.