Triple

T1694148
Position Surface form Disambiguated ID Type / Status
Subject Tula Governorate E36616 entity
Predicate historicalRegion P915 FINISHED
Object Tula region E109563 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: Tula region | Statement: [Tula Governorate, historicalRegion, Tula region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tula region
Context triple: [Tula Governorate, historicalRegion, Tula region]
  • A. Tula Governorate
    Tula Governorate was a historical administrative region of the Russian Empire and early Russian SFSR, located south of Moscow and known for its cultural and literary significance.
  • B. Tula Oblast chosen
    Tula Oblast is a federal subject of Russia located south of Moscow, known for its industrial centers, historical significance, and the city of Tula, famous for samovars and gingerbread.
  • C. Kaluga Oblast
    Kaluga Oblast is a federal subject of western Russia known for its historical cities, space industry heritage, and location southwest of Moscow.
  • D. Vladimir Oblast
    Vladimir Oblast is a federal subject of central Russia known for its historic cities, including Vladimir and Suzdal, which are part of the Golden Ring.
  • E. Voronezh Oblast
    Voronezh Oblast is a federal subject of Russia in the country’s southwest, known for its administrative center Voronezh and its role as an important agricultural and industrial region.
  • 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_69a886163dec8190859c514232a37a05 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62b228988190a7d19003ddf10ce5 completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7ed8b7a08190a39f4b90fbf68cd9 completed March 9, 2026, 8:03 a.m.
Created at: March 4, 2026, 7:29 p.m.