Triple

T8445104
Position Surface form Disambiguated ID Type / Status
Subject Paris–Brussels E199652 entity
Predicate approximateJourneyTimeMinutes P46906 FINISHED
Object about 80 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: about 80 | Statement: [Paris–Brussels, approximateJourneyTimeMinutes, about 80]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: approximateJourneyTimeMinutes
Context triple: [Paris–Brussels, approximateJourneyTimeMinutes, about 80]
  • A. hasApproximateWalkingTimeTo
    Indicates that there is an estimated or approximate amount of time it takes to walk from one entity to another.
  • B. endTimeApproximate
    Indicates that the recorded end time of an event or action is not exact but an approximate value.
  • C. approximateTravelTimeToSheremetyevo
    Indicates the estimated amount of time it typically takes to travel from a given location to Sheremetyevo.
  • D. travelTimeTypical chosen
    Indicates the usual or expected amount of time it takes to travel between two locations under normal conditions.
  • E. travelTimeCategory
    Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
  • F. None of above.

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_69ca83170f9081909cd98f55614c6476 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe3138ee08190918cd82adbe2d9a1 completed March 31, 2026, 3:06 p.m.
PD Predicate disambiguation batch_69cbd0f5a3648190beb53a139a2d5482 completed March 31, 2026, 1:49 p.m.
Created at: March 30, 2026, 6:09 p.m.