Triple

T9313984
Position Surface form Disambiguated ID Type / Status
Subject Immortal Regiment marches E224072 entity
Predicate originatedInCity P1041 FINISHED
Object Tomsk E208233 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: Tomsk | Statement: [Immortal Regiment marches, originatedInCity, Tomsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tomsk
Context triple: [Immortal Regiment marches, originatedInCity, Tomsk]
  • A. Tomsk chosen
    Tomsk is a historic university and research city in southwestern Siberia, known as one of the region’s oldest and most important cultural and educational centers.
  • B. Omsk
    Omsk is one of the largest cities in southwestern Siberia, Russia, serving as a major industrial, cultural, and transportation hub on the Irtysh River.
  • C. Novosibirsk
    Novosibirsk is a major city in southwestern Siberia and the third-largest city in Russia, known as an important industrial, scientific, and cultural center.
  • D. Tobolsk
    Tobolsk is a historic Siberian town in Russia known for its Kremlin and as a place of exile and imprisonment during the late imperial period.
  • E. Volokolamsk
    Volokolamsk is a historic town in western Russia, located northwest of Moscow and known for its medieval origins and role in regional trade and defense.
  • 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_69ca8425f4fc81909c1c586e9a5b7530 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd20b048a081909fd7ec0b6b863063 completed April 1, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bca63c3c819084aec1c0bb962ffe completed April 5, 2026, 1:36 a.m.
Created at: March 30, 2026, 7:37 p.m.