Triple

T906631
Position Surface form Disambiguated ID Type / Status
Subject Francoist Spain E19561 entity
Predicate womenRightsPolicy P277 FINISHED
Object severe legal and social restrictions on women 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: severe legal and social restrictions on women | Statement: [Francoist Spain, womenRightsPolicy, severe legal and social restrictions on women]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: womenRightsPolicy
Context triple: [Francoist Spain, womenRightsPolicy, severe legal and social restrictions on women]
  • A. hasGenderPolicy chosen
    Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
  • B. stanceOnWomenInMinistry
    Indicates a subject’s position or viewpoint regarding the role and participation of women in ministry or religious leadership.
  • C. suffrage
    Indicates that an entity has the right or privilege to vote in political or organizational decision-making processes.
  • D. 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.
  • E. commonPolicyArea
    Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
  • 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_69a4939e889c8190ac148b3ac1a7f90b completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3bcad2481908b83575b2fb80d14 completed March 1, 2026, 9:46 p.m.
PD Predicate disambiguation batch_69a4b28ff5948190982c4439eadf9d87 completed March 1, 2026, 9:41 p.m.
Created at: March 1, 2026, 7:39 p.m.