Triple

T8011576
Position Surface form Disambiguated ID Type / Status
Subject Moscow Governorate E186504 entity
Predicate hasMajorCity 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: [Moscow Governorate, hasMajorCity, Tula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tula
Context triple: [Moscow Governorate, hasMajorCity, Tula]
  • A. Tula
    Tula is a town in the Logudoro region of northern Sardinia, Italy, known for its rural landscape and traditional Sardinian culture.
  • B. 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.
  • C. Tula
    Tula is an important ancient Mesoamerican city, once a major Toltec capital known for its monumental architecture and iconic stone warrior statues.
  • D. Tula
    Tula is the birth name of American actress and dancer Cyd Charisse, famed for her roles in classic Hollywood musicals.
  • E. Tula
    Tula is a small coastal village in the Eastern District of American Samoa known for its traditional Samoan culture and scenic Pacific island setting.
  • 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_69ca82abaffc8190ab8af79cdbc31ab3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3d722fbc8190b22745b581421f16 completed March 31, 2026, 3:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56acfcf88190a0e694f60f2907d2 completed March 31, 2026, 11:20 p.m.
Created at: March 30, 2026, 5:19 p.m.