Triple

T12676804
Position Surface form Disambiguated ID Type / Status
Subject Moscow–Alma-Ata route E302834 entity
Predicate endPoint P390 FINISHED
Object Alma-Ata E50745 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: Alma-Ata | Statement: [Moscow–Alma-Ata route, endPoint, Alma-Ata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alma-Ata
Context triple: [Moscow–Alma-Ata route, endPoint, Alma-Ata]
  • A. Alma-Atinskaya
    Alma-Atinskaya is a southern terminus station of the Moscow Metro, serving as one endpoint of the Zamoskvoretskaya Line.
  • B. Karaganda
    Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
  • C. Syktyvkar
    Syktyvkar is the capital city of the Komi Republic in northwestern Russia, known as an administrative, cultural, and economic center of the region.
  • D. Almaty chosen
    Almaty is the largest city and main commercial and cultural center of Kazakhstan, located in the country’s mountainous southeast.
  • E. Yoshkar-Ola
    Yoshkar-Ola is a city in central Russia that serves as the administrative, cultural, and economic center of the Mari El 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961b0d9c88190a05d6cbcb7a1642d completed April 10, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd084d94081909ae911fce5640aaf completed May 7, 2026, 5:48 p.m.
Created at: April 9, 2026, 5:20 p.m.