Triple

T18491325
Position Surface form Disambiguated ID Type / Status
Subject Thomas Linacre E451822 entity
Predicate tookHolyOrders P14734 FINISHED
Object yes 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: yes | Statement: [Thomas Linacre, tookHolyOrders, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: tookHolyOrders
Context triple: [Thomas Linacre, tookHolyOrders, yes]
  • A. tookReligiousVows
    Indicates that an entity formally committed to a religious life by taking recognized vows within a religious tradition.
  • B. ordainedIn
    Indicates that an individual was formally appointed or consecrated to a religious office or role at a specific place or within a particular institution.
  • C. tookReligiousVowsOn
    Indicates that an entity formally committed to religious vows on a specific date or occasion.
  • D. ordainedFor
    Indicates that one entity has been formally appointed or consecrated to serve, function, or act on behalf of another entity or purpose.
  • E. wasOrdainedAs chosen
    Indicates that an entity was formally appointed or consecrated into an official religious or ceremonial role.
  • 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_69d8d3855d50819097fc8561b0299dd9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e531dcac3c8190b2ebd129ca7f368d completed April 19, 2026, 7:49 p.m.
PD Predicate disambiguation batch_69e469d671088190b619de96ea6f92ab completed April 19, 2026, 5:36 a.m.
Created at: April 10, 2026, 11:35 a.m.