Triple

T3948453
Position Surface form Disambiguated ID Type / Status
Subject Supreme Civil and Criminal Court of Greece E84802 entity
Predicate hasDecisionEffect P14171 FINISHED
Object binding on lower civil courts 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: binding on lower civil courts | Statement: [Supreme Civil and Criminal Court of Greece, hasDecisionEffect, binding on lower civil courts]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDecisionEffect
Context triple: [Supreme Civil and Criminal Court of Greece, hasDecisionEffect, binding on lower civil courts]
  • A. decisionEffect chosen
    Indicates that one decision leads to, influences, or determines a particular outcome or consequence.
  • B. hasIntendedEffect
    Indicates that one entity is expected or designed to produce a particular effect or outcome on another entity or context.
  • C. hasDecisionPoint
    Indicates that there is a specific moment or juncture at which a choice between alternative options or paths must be made.
  • D. hasLegalEffect
    Indicates that an action, document, or condition produces recognized legal consequences or enforceable rights and obligations.
  • E. tookEffect
    Indicates that a change, rule, condition, or event became active, operative, or started producing its intended consequences.
  • 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_69aed934fbfc8190847068e4546de963 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefaa5afdc8190b709af2473d75d02 completed March 9, 2026, 4:51 p.m.
PD Predicate disambiguation batch_69aef8ed04e4819096bced8971cd888d completed March 9, 2026, 4:44 p.m.
Created at: March 9, 2026, 3:30 p.m.