Triple

T10166093
Position Surface form Disambiguated ID Type / Status
Subject Mishnah Bikkurim E235207 entity
Predicate concernsLaw P69180 FINISHED
Object laws of first fruits 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: laws of first fruits | Statement: [Mishnah Bikkurim, concernsLaw, laws of first fruits]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: concernsLaw
Context triple: [Mishnah Bikkurim, concernsLaw, laws of first fruits]
  • A. legalMatters
    Indicates that one entity is involved with, concerned about, or responsible for legal issues, processes, or obligations related to another entity or context.
  • B. concernsClause
    Indicates that one entity (such as a document, statement, or discussion) is about, relates to, or addresses a particular clause.
  • C. concernsRight
    Indicates that something is about or relates specifically to a legal or moral right held by an entity.
  • D. hasLawTheme chosen
    Indicates that something is related to, concerned with, or thematically focused on law or legal matters.
  • E. legalCaseRelatedTo
    Indicates that there is a relevant connection or association between a legal case and another entity, such as a person, organization, event, or legal matter.
  • 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_69ca84ceafd0819085828600e11bed6b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec6cf27481909f38839452ac0e37 completed April 2, 2026, 4:11 a.m.
PD Predicate disambiguation batch_69cd4ba9956c8190a3e15d091e33149d completed April 1, 2026, 4:45 p.m.
Created at: March 30, 2026, 9:10 p.m.