Triple

T14391382
Position Surface form Disambiguated ID Type / Status
Subject New York City Geographic District #10 E356849 entity
Predicate governmentSector P59529 FINISHED
Object public education 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: public education | Statement: [New York City Geographic District #10, governmentSector, public education]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: governmentSector
Context triple: [New York City Geographic District #10, governmentSector, public education]
  • A. governmentCategory
    Indicates the type or classification of a government associated with an entity.
  • B. governmentOffice
    Indicates that an entity functions as an official administrative or governmental office responsible for carrying out public or state-related duties.
  • C. governmentAdministration
    Indicates that an entity is responsible for managing, directing, or overseeing the operations, policies, and functions of a government or public authority.
  • D. budgetarySector chosen
    Indicates that an entity belongs to, is funded through, or is managed within a particular government or organizational budgetary sector.
  • E. governmentBranch
    Indicates that one entity functions as an official division or branch within the structure of a government.
  • 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de902b9acc8190817ffa848a76a880 completed April 14, 2026, 7:06 p.m.
PD Predicate disambiguation batch_69de2aa024c48190805df6a9d63deb10 completed April 14, 2026, 11:53 a.m.
Created at: April 10, 2026, 1:16 a.m.