Triple

T8067752
Position Surface form Disambiguated ID Type / Status
Subject French Leave Beach E188287 entity
Predicate approximateTravelTimeFromGovernor'sHarbour P46906 FINISHED
Object about 5 to 10 minutes by car 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 5 to 10 minutes by car | Statement: [French Leave Beach, approximateTravelTimeFromGovernor'sHarbour, about 5 to 10 minutes by car]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: approximateTravelTimeFromGovernor'sHarbour
Context triple: [French Leave Beach, approximateTravelTimeFromGovernor'sHarbour, about 5 to 10 minutes by car]
  • A. hasApproximateWalkingTimeTo
    Indicates that there is an estimated or approximate amount of time it takes to walk from one entity to another.
  • B. travelTimeByFerry
    Indicates the duration required to travel between two locations specifically using a ferry as the mode of transportation.
  • C. travelTimeTypical chosen
    Indicates the usual or expected amount of time it takes to travel between two locations under normal conditions.
  • D. EVAtime
    Indicates a temporal relationship specifying when an electric vehicle (EV)–related event, action, or state occurs or is valid.
  • E. approximateTravelTimeToSheremetyevo
    Indicates the estimated amount of time it typically takes to travel from a given location to Sheremetyevo.
  • 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_69ca82b42674819086840efea12478e5 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ff8a4fc8190a97fc7111ca7ec4d completed March 31, 2026, 3:31 a.m.
PD Predicate disambiguation batch_69cb049cd51c8190bb3b0f503e42fa8d completed March 30, 2026, 11:17 p.m.
Created at: March 30, 2026, 5:27 p.m.