Triple

T3079258
Position Surface form Disambiguated ID Type / Status
Subject Ob River E64213 entity
Predicate passesThrough P225 FINISHED
Object Omsk
Omsk is a major city in southwestern Siberia, Russia, known as an important industrial, cultural, and transportation center.
 E190794 NE FINISHED

How this triple was built (4 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, passesThrough, Omsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Omsk
Context triple: [Ob River, passesThrough, Omsk]
  • A. 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.
  • 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. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Omsk
Triple: [Ob River, passesThrough, Omsk]
Generated description
Omsk is a major city in southwestern Siberia, Russia, known as an important industrial, cultural, and transportation center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Omsk
Target entity description: Omsk is a major city in southwestern Siberia, Russia, known as an important industrial, cultural, and transportation center.
  • 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.

Provenance (5 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_69be9c2aefc08190931de470b930ce34 completed March 21, 2026, 1:24 p.m.
NEDg Description generation batch_69be9dc80ccc8190a0212288ceb60e41 completed March 21, 2026, 1:31 p.m.
NED2 Entity disambiguation (via description) batch_69be9e2f7d20819097cafc8b31d5459c completed March 21, 2026, 1:33 p.m.
Created at: March 8, 2026, 3:02 p.m.