Triple

T16570848
Position Surface form Disambiguated ID Type / Status
Subject TGV Lyria E402577 entity
Predicate formerName P65 FINISHED
Object Lyria E753002 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: Lyria | Statement: [TGV Lyria, formerName, Lyria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lyria
Context triple: [TGV Lyria, formerName, Lyria]
  • A. Lyria chosen
    Lyria is a high-speed international train service brand connecting France and Switzerland, operated in partnership with SNCF Voyageurs.
  • B. Merania
    Merania was a medieval duchy on the Adriatic coast, historically associated with the House of Andechs and various European noble lineages.
  • C. Scordia
    Scordia is a town and comune in eastern Sicily, Italy, known for its agricultural production, particularly citrus fruits.
  • D. Sarazi
    Sarazi is an Indo-Aryan language spoken primarily in the Chenab Valley region of Jammu and Kashmir, India.
  • E. Corabia
    Corabia is a small town in southern Romania, situated on the Danube River in Olt County and known historically as a local port and agricultural center.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35958d49c8190b995188240fb355b completed April 18, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ee8812c81908ef74636bf39d44a completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:16 a.m.