Triple

T3020280
Position Surface form Disambiguated ID Type / Status
Subject Jengish Chokusu E82437 entity
Predicate alsoKnownAs P39 FINISHED
Object Peak Pobeda E82438 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: Peak Pobeda | Statement: [Jengish Chokusu, alsoKnownAs, Peak Pobeda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peak Pobeda
Context triple: [Jengish Chokusu, alsoKnownAs, Peak Pobeda]
  • A. Pik Pobedy chosen
    Pik Pobedy is the highest peak in the Tian Shan mountain range, straddling the border between Kyrgyzstan and China and known for its extreme climbing conditions.
  • B. Park Pobedy
    Park Pobedy is a major Moscow Metro station known for its great depth and role as an important interchange hub in the network.
  • C. Pobeda
    Pobeda is a Russian low-cost airline and a subsidiary of Aeroflot, operating domestic and international flights primarily from Moscow.
  • D. Kurskaya
    Kurskaya is a Moscow Metro station on the Koltsevaya (Circle) Line, serving as a major transfer hub in the city’s rapid transit network.
  • E. Krasnov
    Krasnov is a Russian surname borne by various notable figures in military, political, and cultural history.
  • 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_69ad8b1fb34081908c1b873e2b7273e1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a940c048190bc46e2c8001db8c0 completed March 8, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e73b5988190be0712f4ddea92f7 completed March 11, 2026, 8:57 a.m.
Created at: March 8, 2026, 3 p.m.