Triple

T3983776
Position Surface form Disambiguated ID Type / Status
Subject Paris public transport network E86820 entity
Predicate hasComponent P35 FINISHED
Object Orlybus E342709 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: Orlybus | Statement: [Paris public transport network, hasComponent, Orlybus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orlybus
Context triple: [Paris public transport network, hasComponent, Orlybus]
  • A. Orlybus chosen
    Orlybus is a dedicated airport shuttle bus service connecting central Paris with Orly Airport.
  • B. Borobi
    Borobi is a blue koala character created as the official mascot for the 2018 Commonwealth Games held on Australia's Gold Coast.
  • C. Averostra
    Averostra is a major clade of theropod dinosaurs that includes many of the more derived, often carnivorous lineages such as ceratosaurs and tetanurans.
  • D. Ormur
    Ormur is a lesser-known Eastern Iranian language spoken primarily by the Ormur people in parts of Afghanistan and Pakistan.
  • E. Bergalia
    Bergalia is a small rural locality in New South Wales, Australia, situated near the coastal town of Moruya.
  • 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_69aed93fd9d4819085d3b2137d2346cb completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef9de58d48190969f354a1bf0df94 completed March 9, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c4a769c819097fb9bfd5890a4f9 completed March 14, 2026, 11:53 a.m.
Created at: March 9, 2026, 3:33 p.m.