Triple

T2773262
Position Surface form Disambiguated ID Type / Status
Subject Tupolev Tu-114 E61507 entity
Predicate usedOnRoute P21808 FINISHED
Object Moscow–Paris
Moscow–Paris is a major international air route linking the capitals of Russia and France.
 E298815 NE FINISHED

How this triple was built (4 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: Moscow–Paris | Statement: [Tupolev Tu-114, usedOnRoute, Moscow–Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Moscow–Paris
Context triple: [Tupolev Tu-114, usedOnRoute, Moscow–Paris]
  • A. Moscow–New York
    Moscow–New York was a prominent long-haul transatlantic air route connecting the Soviet capital with the United States’ largest city during the Cold War era.
  • B. London–Paris
    London–Paris is a major international rail route connecting the capitals of the United Kingdom and France via the Channel Tunnel.
  • C. Moscow–Tokyo
    Moscow–Tokyo refers to the long-haul international air route connecting the capitals of Russia and Japan.
  • D. New York–Paris
    New York–Paris is a major transatlantic air route connecting the United States and France, linking New York City with the French capital.
  • E. Moscow–Delhi
    Moscow–Delhi is an international air route connecting the capitals of Russia and India, historically notable for being served by long-range Soviet aircraft such as the Tupolev Tu-114.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Moscow–Paris
Triple: [Tupolev Tu-114, usedOnRoute, Moscow–Paris]
Generated description
Moscow–Paris is a major international air route linking the capitals of Russia and France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Moscow–Paris
Target entity description: Moscow–Paris is a major international air route linking the capitals of Russia and France.
  • A. Moscow–New York
    Moscow–New York was a prominent long-haul transatlantic air route connecting the Soviet capital with the United States’ largest city during the Cold War era.
  • B. London–Paris
    London–Paris is a major international rail route connecting the capitals of the United Kingdom and France via the Channel Tunnel.
  • C. Moscow–Tokyo
    Moscow–Tokyo refers to the long-haul international air route connecting the capitals of Russia and Japan.
  • D. New York–Paris
    New York–Paris is a major transatlantic air route connecting the United States and France, linking New York City with the French capital.
  • E. Moscow–Delhi
    Moscow–Delhi is an international air route connecting the capitals of Russia and India, historically notable for being served by long-range Soviet aircraft such as the Tupolev Tu-114.
  • F. None of above. chosen

Provenance (5 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_69ab4b7cd13481909174bca9809ed259 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abe0895e5881909702e69aaee5c425 completed March 7, 2026, 8:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc64c83748190921589bec20dec58 completed March 10, 2026, 7:20 a.m.
NEDg Description generation batch_69afc6b723f48190b93df0dc2de6c839 completed March 10, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69afc750fee08190bf3c112f6f204af4 completed March 10, 2026, 7:25 a.m.
Created at: March 6, 2026, 9:57 p.m.