Triple

T5807203
Position Surface form Disambiguated ID Type / Status
Subject Noginsk E128774 entity
Predicate administrativeCenterOf P383 FINISHED
Object Noginsky District E568699 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: Noginsky District | Statement: [Noginsk, administrativeCenterOf, Noginsky District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Noginsky District
Context triple: [Noginsk, administrativeCenterOf, Noginsky District]
  • A. Noginsky District chosen
    Noginsky District is an administrative and municipal district in Moscow Oblast, Russia, centered around the town of Noginsk and encompassing surrounding settlements.
  • B. Zavitinsky District
    Zavitinsky District is an administrative and municipal district in Amur Oblast, Russia, centered around the town of Zavitinsk.
  • C. Yurinsky District
    Yurinsky District is an administrative and municipal district in the Mari El Republic of Russia, characterized by its rural settlements and small population.
  • D. Nikolaevsky District
    Nikolaevsky District is an administrative and municipal district located within Khabarovsk Krai in the Russian Far East.
  • E. Tikhvinsky District
    Tikhvinsky District is an administrative and municipal district in Leningrad Oblast, Russia, known for its historical towns and location in the eastern part of the region.
  • 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_69c00846a0d881909e46841f8e156b64 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02b17417081908779741b9bfbb720 completed March 22, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c135397abc8190b9c10974983be44d completed March 23, 2026, 12:42 p.m.
Created at: March 22, 2026, 3:52 p.m.