Triple

T8720171
Position Surface form Disambiguated ID Type / Status
Subject Line 1 (Paris Métro) E206989 entity
Predicate servesStation P839 FINISHED
Object Nation E65648 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: Nation | Statement: [Line 1 (Paris Métro), servesStation, Nation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nation
Context triple: [Line 1 (Paris Métro), servesStation, Nation]
  • A. Nation chosen
    Nation is a major public square and transportation hub in eastern Paris, France, known for its large roundabout, prominent monuments, and busy metro and RER interchange.
  • B. Nation
    Nation is a common English surname shared by various individuals, including notable figures in entertainment and public life.
  • C. National
    National is a major centre-right political party in New Zealand, formally known as the New Zealand National Party.
  • D. National
    National is a Japanese electronics and home appliance brand historically used by Panasonic for a wide range of consumer products, especially in Asian markets.
  • E. Nacional
    Nacional is a news section of the Colombian newspaper El Espectador that focuses on national-level events and issues.
  • 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_69ca835811d8819081ea00fd2a2c9a1c completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d02a52c81909f93622ae6920b80 completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf28f599a481908e93bc5b5c41296e completed April 3, 2026, 2:41 a.m.
Created at: March 30, 2026, 6:36 p.m.