Triple

T18446305
Position Surface form Disambiguated ID Type / Status
Subject Russian Empire in the Caucasus E450666 entity
Predicate hasPart P35 FINISHED
Object Kutaisi Governorate 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: Kutaisi Governorate | Statement: [Russian Empire in the Caucasus, hasPart, Kutaisi Governorate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kutaisi Governorate
Context triple: [Russian Empire in the Caucasus, hasPart, Kutaisi Governorate]
  • A. Kutais Governorate chosen
    Kutais Governorate was an administrative division of the Russian Empire in the Caucasus region, centered around the city of Kutaisi in what is now western Georgia.
  • B. Yala
    Yala is a language spoken by the Yala people of Cross River State in southeastern Nigeria.
  • C. Yala
    Yala is another name for Patan, a historic city in Nepal renowned for its rich Newar culture, traditional arts, and intricately designed temples and palaces.
  • D. Yala
    Yala is a major city in Thailand’s deep south, known as an administrative, commercial, and cultural center near the Malaysian border.
  • E. Shaqra Governorate
    Shaqra Governorate is an administrative region and town in central Saudi Arabia known for its historical architecture and location within Riyadh Province.
  • 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e52644959c8190b1117608e5fa15aa completed April 19, 2026, 7 p.m.
Created at: April 10, 2026, 11:30 a.m.