Triple

T7460677
Position Surface form Disambiguated ID Type / Status
Subject Office of Documents and Administrative Issuances E176238 entity
Predicate typeOfDocumentsHandled P27701 FINISHED
Object legal documents 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: legal documents | Statement: [Office of Documents and Administrative Issuances, typeOfDocumentsHandled, legal documents]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typeOfDocumentsHandled
Context triple: [Office of Documents and Administrative Issuances, typeOfDocumentsHandled, legal documents]
  • A. typeOfCasesHandled
    Indicates the categories or kinds of cases that an entity (such as a person, organization, or system) is responsible for managing or processing.
  • B. legalTextTypeWorkedOn chosen
    Indicates that an entity has worked on or handled a specific type or category of legal text.
  • C. typeOfJurisdictionDocument
    Indicates the specific kind or category of jurisdiction-related document associated with an entity or legal context.
  • D. documentationType
    Indicates the specific category or kind of documentation associated with or required for an entity or process.
  • E. typeOfLaw
    Indicates that one entity is a specific category or kind of law to which the other entity pertains.
  • 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_69c69f21632481908bf83f6c6da897e3 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f3d525708190b7838e07ac2fbe1f completed March 27, 2026, 9:17 p.m.
PD Predicate disambiguation batch_69c6f03bad9c8190bdd5abb86d37df47 completed March 27, 2026, 9:01 p.m.
Created at: March 27, 2026, 3:38 p.m.