Triple

T6026118
Position Surface form Disambiguated ID Type / Status
Subject Tatar ASSR E134185 entity
Predicate hasPart P35 FINISHED
Object Naberezhnye Chelny E335486 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: Naberezhnye Chelny | Statement: [Tatar ASSR, hasPart, Naberezhnye Chelny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naberezhnye Chelny
Context triple: [Tatar ASSR, hasPart, Naberezhnye Chelny]
  • A. Naberezhnye Chelny chosen
    Naberezhnye Chelny is a major industrial city in Russia’s Republic of Tatarstan, best known as the home of the KamAZ truck manufacturing plant.
  • B. Kazanh
    Kazanh is a locality within Turkey’s Ankara Province, situated in the Central Anatolia region.
  • C. Makhachkala
    Makhachkala is the largest city and main political, economic, and cultural center of the Russian republic of Dagestan, located on the western shore of the Caspian Sea.
  • D. Cheboksary
    Cheboksary is a major city on the Volga River in western Russia and the capital of the Chuvash Republic.
  • E. Kazan
    Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
  • 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_69c0087515148190a97475d412563865 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04fc08c5c819085afab5b18bce4d1 completed March 22, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6409d48408190b2048c07272277ac completed March 27, 2026, 8:32 a.m.
Created at: March 22, 2026, 4:07 p.m.