Triple

T35362680
Position Surface form Disambiguated ID Type / Status
Subject Kuala Perlis Ferry Terminal E1021535 entity
Predicate hasApproximateTravelTimeToLangkawi P177302 FINISHED
Object about 1 hour to 1.5 hours 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 1 hour to 1.5 hours | Statement: [Kuala Perlis Ferry Terminal, hasApproximateTravelTimeToLangkawi, about 1 hour to 1.5 hours]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasApproximateTravelTimeToLangkawi
Context triple: [Kuala Perlis Ferry Terminal, hasApproximateTravelTimeToLangkawi, about 1 hour to 1.5 hours]
  • A. travelTimeFromKotaKinabalu
    Indicates the amount of time required to travel from Kota Kinabalu to another specified location or entity.
  • B. travelTimeToKLsentral
    Indicates the amount of time required to travel from a given location to KL Sentral.
  • C. hasApproximateTravelTimeToMainland chosen
    Indicates that one location is associated with an estimated or approximate amount of time required to travel from it to the mainland.
  • D. travelTimeFromLabuanBajo
    Indicates the amount of time required to travel from Labuan Bajo to another specified location or entity.
  • E. hasApproximateWalkingTimeTo
    Indicates that there is an estimated or approximate amount of time it takes to walk from one entity to another.
  • 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_69f76def44c881908a20e8008572eb44 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fde49a084081909d99b1e0258169d5 completed May 8, 2026, 1:26 p.m.
PD Predicate disambiguation batch_69fde1d04bd881909a46ecbbf18dfe59 completed May 8, 2026, 1:14 p.m.
Created at: May 3, 2026, 4:03 p.m.