Triple

T10160960
Position Surface form Disambiguated ID Type / Status
Subject Terengganu State Legislative Assembly E233887 entity
Predicate meetsType P92352 FINISHED
Object plenary sessions 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: plenary sessions | Statement: [Terengganu State Legislative Assembly, meetsType, plenary sessions]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: meetsType
Context triple: [Terengganu State Legislative Assembly, meetsType, plenary sessions]
  • A. meetsTo
    Indicates that one entity comes together with another at a specific time and place for an encounter, appointment, or interaction.
  • B. meets
    Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
  • C. meetsAs
    Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
  • D. meetsUnder
    Indicates that one entity encounters or comes together with another entity in a context where it is subordinate to, governed by, or occurring within the scope or authority of a third entity or condition.
  • E. meetsEvery
    Indicates that one entity encounters or comes into contact with every member of a specified set of entities.
  • F. None of above. chosen

Provenance (4 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_69ca848e80748190b91d1e04d35512c7 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdec59b01081908be6ca37dc575465 completed April 2, 2026, 4:11 a.m.
PD Predicate disambiguation batch_69cd4ba795808190acc9124c98c6e40f completed April 1, 2026, 4:45 p.m.
PDg Predicate description generation batch_69cd4f8f869c8190a82ad040993e0244 completed April 1, 2026, 5:02 p.m.
Created at: March 30, 2026, 9:09 p.m.