Triple

T3079284
Position Surface form Disambiguated ID Type / Status
Subject Ob River E64213 entity
Predicate associatedCity P3207 FINISHED
Object Omsk E190794 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: Omsk | Statement: [Ob River, associatedCity, Omsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Omsk
Context triple: [Ob River, associatedCity, Omsk]
  • A. Omsk chosen
    Omsk is one of the largest cities in southwestern Siberia, Russia, serving as a major industrial, cultural, and transportation hub on the Irtysh River.
  • B. Barnaul
    Barnaul is a significant industrial and cultural city in southwestern Siberia, Russia, located near the Ob River and serving as a key regional center.
  • C. Krasnoyarsk
    Krasnoyarsk is a large industrial and cultural city in central Russia, situated on the Yenisei River and known as one of the key urban centers of Siberia.
  • D. Irkutsk
    Irkutsk is a major city in southeastern Siberia, Russia, historically significant as a political and administrative center and a key hub during the Russian Civil War.
  • E. Tomsk
    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.
  • 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_69ad857bb4c88190a4cf27893fcabed8 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada1a86a848190a47ca127cc7e6326 completed March 8, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69bec330d09c819085930d71b21acb7c completed March 21, 2026, 4:11 p.m.
Created at: March 8, 2026, 3:02 p.m.