Triple

T26033336
Position Surface form Disambiguated ID Type / Status
Subject June 1968 French legislative election E647488 entity
Predicate resultEffectOnLeft P168047 FINISHED
Object significant losses for left-wing parties 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: significant losses for left-wing parties | Statement: [June 1968 French legislative election, resultEffectOnLeft, significant losses for left-wing parties]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: resultEffectOnLeft
Context triple: [June 1968 French legislative election, resultEffectOnLeft, significant losses for left-wing parties]
  • A. effectOnOutput
    Indicates how one factor, action, or condition influences or changes the resulting output of a process or system.
  • B. tookEffect
    Indicates that a change, rule, condition, or event became active, operative, or started producing its intended consequences.
  • C. canonicalEffect
    Indicates the standard or primary effect that an action, event, or entity is typically understood to produce.
  • D. sideEffect
    Indicates that one entity is an unintended or secondary effect resulting from the use or occurrence of another entity.
  • E. effectOnUnion
    Indicates the impact or influence that something has on a union as a whole.
  • 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_69e77e8b60e88190a3b26c4f0032a2c2 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f673633d288190b52ceb9f8a057c44 completed May 2, 2026, 9:57 p.m.
PD Predicate disambiguation batch_69f66ec3d3d48190ab2f2b71939e572e completed May 2, 2026, 9:38 p.m.
PDg Predicate description generation batch_69f67256d064819094be04fc1bbbc635 completed May 2, 2026, 9:53 p.m.
Created at: April 22, 2026, 9:06 a.m.