Triple

T1645844
Position Surface form Disambiguated ID Type / Status
Subject National Assembly of Pakistan E35579 entity
Predicate hasReservedSeatsForWomen P9399 FINISHED
Object 60 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: 60 | Statement: [National Assembly of Pakistan, hasReservedSeatsForWomen, 60]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasReservedSeatsForWomen
Context triple: [National Assembly of Pakistan, hasReservedSeatsForWomen, 60]
  • A. hasReservedSeats chosen
    Indicates that specific seats have been set aside or allocated in advance for a particular entity or purpose.
  • B. hasSeat
    Indicates that one entity possesses, provides, or includes a seat for another entity.
  • C. hasClubSeats
    Indicates that an entity (such as a venue or section) includes or is equipped with club-level seating.
  • D. hasSecondSeat
    Indicates that an entity possesses or includes a secondary seat in addition to a primary one.
  • E. hasSeating
    Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a919306fd48190a245fc95e0e759d9 completed March 5, 2026, 5:48 a.m.
PD Predicate disambiguation batch_69a907cc9d348190b76b0d3f596e5a81 completed March 5, 2026, 4:34 a.m.
Created at: March 4, 2026, 7:28 p.m.