Triple

T9106580
Position Surface form Disambiguated ID Type / Status
Subject Privatization Program E218491 entity
Predicate linkedPolicy P48852 FINISHED
Object fiscal reform in Saudi Arabia 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: fiscal reform in Saudi Arabia | Statement: [Privatization Program, linkedPolicy, fiscal reform in Saudi Arabia]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: linkedPolicy
Context triple: [Privatization Program, linkedPolicy, fiscal reform in Saudi Arabia]
  • A. linkedToPolicy chosen
    Indicates that an entity is associated or connected to a specific policy, such that the policy governs, influences, or is relevant to that entity.
  • B. associatedPolis
    Indicates a relationship where an entity is linked or connected to a particular city-state (polis), typically as its relevant or related political unit.
  • C. linkedPractice
    Indicates that one practice is associated or connected to another practice in a meaningful or relevant way.
  • D. linkedProgram
    Indicates that one program is associated or connected to another program in a meaningful or dependent way.
  • E. linkedLocation
    Indicates that one location is associated or connected to another location in a meaningful way, such as being related, referenced, or contextually tied.
  • 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_69ca83db7448819090d0a5de842ef2ac completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca57286a88190b256d2461c5c0aed completed April 1, 2026, 4:56 a.m.
PD Predicate disambiguation batch_69cc65fe5be081909d4470d6317b14a6 completed April 1, 2026, 12:25 a.m.
Created at: March 30, 2026, 7:16 p.m.