Triple

T38329111
Position Surface form Disambiguated ID Type / Status
Subject Al Riffa–Mall of Qatar metro station E1036870 entity
Predicate hasTicketingHall P27344 FINISHED
Object yes 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: yes | Statement: [Al Riffa–Mall of Qatar metro station, hasTicketingHall, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTicketingHall
Context triple: [Al Riffa–Mall of Qatar metro station, hasTicketingHall, yes]
  • A. hasTicketHall chosen
    Indicates that a place or facility includes or is equipped with a designated ticket hall area for purchasing or validating tickets.
  • B. hasTicketing
    Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
  • C. hasTicketHallDesign
    Indicates that an entity possesses or is characterized by a particular design or layout of its ticket hall.
  • D. hasTicketBooths
    Indicates that one entity possesses or contains ticket booths used for selling or distributing tickets.
  • E. hasAuditorium
    Indicates that one entity possesses or includes an auditorium as part of its facilities.
  • 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_69f76e1c16fc8190bde982289dd5106b completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fe8ddf70e48190a917eb9e8f7b6966 completed May 9, 2026, 1:29 a.m.
PD Predicate disambiguation batch_69fe87ef94dc81909bb00ec8d6de9bcd completed May 9, 2026, 1:03 a.m.
Created at: May 3, 2026, 4:30 p.m.