Triple

T3899378
Position Surface form Disambiguated ID Type / Status
Subject Ouigo E90447 entity
Predicate fareModel P52748 FINISHED
Object low-cost LITERAL 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: low-cost | Statement: [Ouigo, fareModel, low-cost]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fareModel
Context triple: [Ouigo, fareModel, low-cost]
  • A. fare
    Indicates the price or cost required for a person or thing to be transported by a particular mode of travel or service.
  • B. fareType
    Indicates the category or class of fare (such as standard, discounted, or promotional) that applies to a given trip, ticket, or pricing instance.
  • C. fareProduct
    Indicates a relationship where a specific fare or price offering is associated with a particular product or service option.
  • D. fareStructure
    Indicates the pricing scheme or set of rules that determine how fares are calculated and applied for a given service or trip.
  • E. fareStructureFeature
    Indicates a characteristic or condition of how fares are structured, calculated, or applied within a pricing or ticketing system.
  • F. None of above. chosen

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_69aed95d315881908cbf1bf4a7215fbf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef1abe2dc81909c18aeae9b286898 completed March 9, 2026, 4:13 p.m.
PD Predicate disambiguation batch_69aee75b5b808190a348a31b1325d3d0 completed March 9, 2026, 3:29 p.m.
PDg Predicate description generation batch_69aef1aada308190821a3dfa6af170b3 completed March 9, 2026, 4:13 p.m.
Created at: March 9, 2026, 3:21 p.m.