Triple

T2438407
Position Surface form Disambiguated ID Type / Status
Subject Kama River E53216 entity
Predicate majorCityOnRiver P316 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: [Kama River, majorCityOnRiver, Naberezhnye Chelny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naberezhnye Chelny
Context triple: [Kama River, majorCityOnRiver, 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. 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.
  • C. 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.
  • D. Grozny
    Grozny is the capital and largest city of the Chechen Republic in southwestern Russia, known for its turbulent recent history and extensive post-war reconstruction.
  • E. Ufa
    Ufa is the capital and largest city of the Republic of Bashkortostan in Russia, known as a major industrial, cultural, and economic center in the Ural 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_69ab495b6dac8190ac82661aa1452222 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc9f4d2dc8190b3c264a6c20d1bd5 completed March 7, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69b4e4c13494819095821f44916329c9 completed March 14, 2026, 4:32 a.m.
Created at: March 6, 2026, 9:43 p.m.