Triple

T2767135
Position Surface form Disambiguated ID Type / Status
Subject Government of Punjab E61363 entity
Predicate numberOfAssemblySeats P11035 FINISHED
Object 117 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: 117 | Statement: [Government of Punjab, numberOfAssemblySeats, 117]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: numberOfAssemblySeats
Context triple: [Government of Punjab, numberOfAssemblySeats, 117]
  • A. legislativeAssemblySeats chosen
    Indicates the number of seats an entity holds or is allocated in a legislative assembly.
  • B. numberOfSeatsWon
    Indicates the quantity of seats secured by an entity (such as a party or candidate) in an election or representative body.
  • C. numberOfElectedMembers
    Indicates the total count of individuals who have been formally chosen through an election to serve as members of a given body or group.
  • D. legislativeCouncilSeats
    Indicates the number of seats held or allocated in a legislative council within a given political or administrative context.
  • E. proportionalRepresentationSeats
    Indicates that the number of seats allocated to an entity is determined according to a proportional representation system based on its share of votes or support.
  • 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_69ab4b7bab6c8190a5c2efef19a8ef34 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abddceb9d88190961e30d521a21552 completed March 7, 2026, 8:11 a.m.
PD Predicate disambiguation batch_69abdcfc5e1c8190a5ac2c48d3eaeb0a completed March 7, 2026, 8:08 a.m.
Created at: March 6, 2026, 9:57 p.m.