Triple

T2563750
Position Surface form Disambiguated ID Type / Status
Subject Lambeth 1930 Resolution on contraception E57301 entity
Predicate moralCondition P16129 FINISHED
Object serious moral reasons 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: serious moral reasons | Statement: [Lambeth 1930 Resolution on contraception, moralCondition, serious moral reasons]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: moralCondition
Context triple: [Lambeth 1930 Resolution on contraception, moralCondition, serious moral reasons]
  • A. moralStatus
    Indicates the ethical standing or degree of moral consideration that one entity has in relation to another.
  • B. moralExpectation
    Indicates that one entity is expected, by moral or ethical standards, to behave in a certain way toward another entity or in a given situation.
  • C. moralImplication chosen
    Indicates that one situation, action, or state of affairs entails or suggests a particular moral judgment, obligation, or ethical consequence.
  • D. derivesMoralityFrom
    Indicates that one entity bases or grounds its moral principles, judgments, or ethical framework on another entity.
  • E. moralTheme
    Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
  • 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.