Triple

T20321107
Position Surface form Disambiguated ID Type / Status
Subject Commentaries of Rashi on Mishnah Berakhot E492207 entity
Predicate approachToLanguage P56443 FINISHED
Object explanation of Aramaic and rare Hebrew terms 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: explanation of Aramaic and rare Hebrew terms | Statement: [Commentaries of Rashi on Mishnah Berakhot, approachToLanguage, explanation of Aramaic and rare Hebrew terms]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: approachToLanguage
Context triple: [Commentaries of Rashi on Mishnah Berakhot, approachToLanguage, explanation of Aramaic and rare Hebrew terms]
  • A. focusesOnLanguage chosen
    Indicates that an entity’s primary attention, activity, or content is directed toward language as its main subject or concern.
  • B. learnsLanguageFrom
    Indicates that one entity acquires or improves knowledge of a language through instruction, exposure, or guidance provided by another entity.
  • C. languageOfDevelopment
    Indicates the programming or natural language used to develop, implement, or create a given entity.
  • D. languageAcquisitionContext
    Indicates the situational or environmental context in which an entity learns or acquires a language.
  • E. recommendsLanguage
    Indicates that one entity suggests or endorses a particular language for use by another entity or in a specific context.
  • 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_69e0b4a0134081909113563e1c3ba68a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6778b8b648190b80badaf15be2599 completed April 20, 2026, 6:59 p.m.
PD Predicate disambiguation batch_69e5762655ac8190a8cc48a29fa2c0c4 completed April 20, 2026, 12:41 a.m.
Created at: April 16, 2026, 11:20 a.m.