Triple

T4015458
Position Surface form Disambiguated ID Type / Status
Subject Central Economic Region of Russia E90744 entity
Predicate includesMajorCity P316 FINISHED
Object Tula E111344 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 | Statement: [Central Economic Region of Russia, includesMajorCity, Tula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tula
Context triple: [Central Economic Region of Russia, includesMajorCity, Tula]
  • A. Tula chosen
    Tula is a historic Russian city south of Moscow, known for its metalworking, samovar production, and as a cultural center near Leo Tolstoy’s estate at Yasnaya Polyana.
  • B. Tula
    Tula is an important ancient Mesoamerican city, once a major Toltec capital known for its monumental architecture and iconic stone warrior statues.
  • C. Tula
    Tula is the birth name of American actress and dancer Cyd Charisse, famed for her roles in classic Hollywood musicals.
  • D. Tenosique
    Tenosique is a municipality and city in southeastern Mexico known for its location in the state of Tabasco near the Guatemalan border and along key migration routes.
  • E. Sabinas
    Sabinas is a municipality and city in the northern Mexican state of Coahuila, known historically for its coal mining and regional agricultural activities.
  • 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_69aed95e44088190aff7d90a151b1b20 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefaa7352481908232534c89a698e7 completed March 9, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c768e5481908b184332e3c73588 completed March 14, 2026, 11:54 a.m.
Created at: March 9, 2026, 3:35 p.m.