Triple

T5882113
Position Surface form Disambiguated ID Type / Status
Subject Tatarstan Academy of Sciences E130772 entity
Predicate headquartersLocation P62 FINISHED
Object Kazan E35521 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: Kazan | Statement: [Tatarstan Academy of Sciences, headquartersLocation, Kazan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kazan
Context triple: [Tatarstan Academy of Sciences, headquartersLocation, Kazan]
  • A. Kazan chosen
    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.
  • B. Kazanh
    Kazanh is a locality within Turkey’s Ankara Province, situated in the Central Anatolia region.
  • C. 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.
  • D. Naberezhnye Chelny
    Naberezhnye Chelny is a major industrial city in Russia’s Republic of Tatarstan, best known as the home of the KamAZ truck manufacturing plant.
  • E. Cheboksary
    Cheboksary is a major city on the Volga River in western Russia and the capital of the Chuvash Republic.
  • 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_69c0085523688190bfd487479ce819e6 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03673ecd88190978993056b675259 completed March 22, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20d216ca481908791d8e891cd3e3a completed March 24, 2026, 4:03 a.m.
Created at: March 22, 2026, 3:57 p.m.