Triple

T34211631
Position Surface form Disambiguated ID Type / Status
Subject Muskerry Gaeltacht E877671 entity
Predicate governmentPolicyArea P148602 FINISHED
Object Irish language preservation 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: Irish language preservation | Statement: [Muskerry Gaeltacht, governmentPolicyArea, Irish language preservation]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: governmentPolicyArea
Context triple: [Muskerry Gaeltacht, governmentPolicyArea, Irish language preservation]
  • A. policyFocus
    Indicates that an entity (such as a person, organization, or document) is primarily concerned with, directed toward, or centered on a particular policy area or issue.
  • B. commonPolicyArea
    Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
  • C. policyTopic chosen
    Indicates that one entity is about, concerned with, or categorized under a particular policy-related subject or theme.
  • D. economicPolicyArea
    Indicates the specific domain or sector of economic policy to which an action, measure, or issue is related.
  • E. influencedPolicyArea
    Indicates that one entity has affected, shaped, or guided the development, direction, or implementation of a particular policy area associated with another entity.
  • 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_69f349b0b4bc819088c1552424089ee9 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_6a00dc330b148190aaae2ac6a5327960 completed May 10, 2026, 7:27 p.m.
PD Predicate disambiguation batch_6a00d9d2904881909dafbfe7b9e5ad81 completed May 10, 2026, 7:17 p.m.
Created at: May 1, 2026, 1:55 a.m.