Triple

T15744077
Position Surface form Disambiguated ID Type / Status
Subject Theodore Lyman III E381673 entity
Predicate civicReformFocus P1876 FINISHED
Object urban governance improvements 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: urban governance improvements | Statement: [Theodore Lyman III, civicReformFocus, urban governance improvements]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: civicReformFocus
Context triple: [Theodore Lyman III, civicReformFocus, urban governance improvements]
  • A. goalOfReforms
    Indicates that a reform or set of reforms is undertaken with the aim or intended objective of achieving a particular outcome.
  • B. policyFocus chosen
    Indicates that an entity (such as a person, organization, or document) is primarily concerned with, directed toward, or centered on a particular policy area or issue.
  • C. socialReformFocus
    Indicates a focus on changing or improving social structures, policies, or conditions as part of a reform effort.
  • D. constitutionalReformSubject
    Indicates that an entity is the subject or focus of a constitutional reform process, proposal, or change.
  • E. municipalityReform
    Indicates a formal reorganization or restructuring of a municipality’s administrative boundaries, governance, or status.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b4d6b5788190883746ee82c799f5 completed April 16, 2026, 10:07 a.m.
PD Predicate disambiguation batch_69e0052c6208819098165d61d378d13b completed April 15, 2026, 9:37 p.m.
Created at: April 10, 2026, 4:46 a.m.