Triple

T3657787
Position Surface form Disambiguated ID Type / Status
Subject Renault–Gitane E77574 entity
Predicate usedBicyclesFrom P4673 FINISHED
Object Gitane E350546 NE FINISHED

How this triple was built (3 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: Gitane | Statement: [Renault–Gitane, usedBicyclesFrom, Gitane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gitane
Context triple: [Renault–Gitane, usedBicyclesFrom, Gitane]
  • A. Gitane chosen
    Gitane is a French bicycle manufacturer best known for its road racing bikes and historic presence in professional cycling.
  • B. Griante
    Griante is a small lakeside village on Lake Como in Lombardy, Italy, known for its scenic views and historic villas.
  • C. Souletin
    Souletin is a distinct dialect of the Basque language traditionally spoken in the Soule (Zuberoa) region of the French Basque Country.
  • D. Oghi
    Oghi is a town in Pakistan's Khyber Pakhtunkhwa province, known as a local administrative and commercial center within the Hazara region.
  • E. Gilot
    Gilot is a French surname most notably borne by Françoise Gilot, the painter and writer known for her long relationship with Pablo Picasso.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usedBicyclesFrom
Context triple: [Renault–Gitane, usedBicyclesFrom, Gitane]
  • A. bicycleUse
    Indicates that an entity makes use of a bicycle for transportation, activity, or other purposes.
  • B. usedEquipmentFrom chosen
    Indicates that one entity has utilized or operated equipment that originated from or was provided by another entity.
  • C. bicycleType
    Indicates the specific kind or category of bicycle associated with an entity.
  • D. hasRideCycle
    Indicates that one entity is associated with, or participates in, a recurring sequence or cycle of rides or ride operations.
  • E. passesUsedForTransportation
    Indicates that the passes are utilized as a means or instrument for transporting people or goods.
  • F. None of above.

Provenance (4 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_69ad85def5cc8190863dccf55a18bebb completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc3d36c1c8190920397a75de4c47d completed March 8, 2026, 6:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c393f0608190a9af2cdc87bf83d9 completed March 14, 2026, 2:10 a.m.
PD Predicate disambiguation batch_69adb847e9d881909dad2ffd0f3b6c15 completed March 8, 2026, 5:56 p.m.
Created at: March 8, 2026, 3:24 p.m.