Triple

T2563753
Position Surface form Disambiguated ID Type / Status
Subject Lambeth 1930 Resolution on contraception E57301 entity
Predicate positionOnContraception P17839 FINISHED
Object cautious permission within marriage 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: cautious permission within marriage | Statement: [Lambeth 1930 Resolution on contraception, positionOnContraception, cautious permission within marriage]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: positionOnContraception
Context triple: [Lambeth 1930 Resolution on contraception, positionOnContraception, cautious permission within marriage]
  • A. sexControlTechnique
    Indicates a technique or method used to influence, determine, or manipulate the sex of organisms or offspring.
  • B. positionOn
    Indicates that one entity is located on top of or at a specific place along the surface or extent of another entity.
  • C. positionOnReason chosen
    Indicates that one entity holds a particular stance, justification, or rationale concerning another entity or issue.
  • D. positionOnGood
    Indicates the stance or viewpoint an entity holds regarding a particular good, such as support, opposition, or neutrality.
  • E. positionOnLabor
    Indicates the role, stance, or viewpoint an entity holds regarding labor-related issues, policies, or practices.
  • 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_69ab4a4ef9008190a0e6d4422b9418b7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd35c6ee88190b6eaa1841d3e99a4 completed March 7, 2026, 7:27 a.m.
PD Predicate disambiguation batch_69abd0cc8d308190ae7aa32b8f5ae2e5 completed March 7, 2026, 7:16 a.m.
Created at: March 6, 2026, 9:48 p.m.