Triple

T17948519
Position Surface form Disambiguated ID Type / Status
Subject Фрунзенская набережная E448766 entity
Predicate hasNearbyDistrict P4647 FINISHED
Object Хамовники
Хамовники — это исторический и престижный район Москвы в центральной части города, известный своими старыми усадьбами, культурными объектами и развитой городской инфраструктурой.
 E1298920 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: Хамовники | Statement: [Фрунзенская набережная, hasNearbyDistrict, Хамовники]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Хамовники
Context triple: [Фрунзенская набережная, hasNearbyDistrict, Хамовники]
  • A. Novogireyevo
    Novogireyevo is a Moscow Metro station serving the Novogireyevo District in the eastern part of Moscow, Russia.
  • B. Krylatskoye
    Krylatskoye is a Moscow Metro station serving the Krylatskoye District in western Moscow, Russia.
  • C. Митино
    Митино — это станция Московского метрополитена, расположенная в одноимённом районе на северо-западе города.
  • D. Сокольники
    Сокольники is a district in Moscow, Russia, best known for its large historic park and metro station of the same name.
  • E. Sokolniki
    Sokolniki is a Moscow Metro station on the Big Circle Line, serving the Sokolniki District in Russia’s capital.
  • 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: Хамовники
Triple: [Фрунзенская набережная, hasNearbyDistrict, Хамовники]
Generated description
Хамовники — это исторический и престижный район Москвы в центральной части города, известный своими старыми усадьбами, культурными объектами и развитой городской инфраструктурой.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Хамовники
Target entity description: Хамовники — это исторический и престижный район Москвы в центральной части города, известный своими старыми усадьбами, культурными объектами и развитой городской инфраструктурой.
  • A. Novogireyevo
    Novogireyevo is a Moscow Metro station serving the Novogireyevo District in the eastern part of Moscow, Russia.
  • B. Krylatskoye
    Krylatskoye is a Moscow Metro station serving the Krylatskoye District in western Moscow, Russia.
  • C. Митино
    Митино — это станция Московского метрополитена, расположенная в одноимённом районе на северо-западе города.
  • D. Сокольники
    Сокольники is a district in Moscow, Russia, best known for its large historic park and metro station of the same name.
  • E. Sokolniki
    Sokolniki is a Moscow Metro station on the Big Circle Line, serving the Sokolniki District in Russia’s capital.
  • F. None of above. chosen

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_69d8b9f8cca8819099836916c56b7c95 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4afaac780819097434b20b1f155d2 completed April 19, 2026, 10:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0330099eb48190ae81eeceed035c48 completed May 12, 2026, 1:50 p.m.
NEDg Description generation batch_6a03310fd4608190b8c23df661ddc2ad completed May 12, 2026, 1:54 p.m.
NED2 Entity disambiguation (via description) batch_6a03330f373c81908bb2418dfbeec74f completed May 12, 2026, 2:02 p.m.
Created at: April 10, 2026, 10:21 a.m.