Triple

T3061324
Position Surface form Disambiguated ID Type / Status
Subject 1902 Education Act E62001 entity
Predicate affectedLevel P44875 FINISHED
Object local government 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: local government | Statement: [1902 Education Act, affectedLevel, local government]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: affectedLevel
Context triple: [1902 Education Act, affectedLevel, local government]
  • A. representedLevel
    Indicates that one entity denotes or encodes the degree, intensity, or value (i.e., the level) of another entity or property.
  • B. affectedArea
    Indicates the specific region or extent over which an event, condition, or influence has an impact.
  • C. assessmentLevel
    Indicates the degree, rating, or intensity assigned to an evaluation or judgment of something.
  • D. statusLevelAbove
    Indicates that one entity’s status level is higher or more advanced than another entity’s status level.
  • E. affectedFunction
    Indicates that one entity has an impact on, alters, or impairs the operation or behavior of another entity’s function.
  • F. None of above. chosen

Provenance (4 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9e9e1e248190b5ed5ebcdad1321e completed March 8, 2026, 4:06 p.m.
PD Predicate disambiguation batch_69ad962326e081909d5521c3d3ea3158 completed March 8, 2026, 3:30 p.m.
PDg Predicate description generation batch_69ad97f6af3881909f4547967384114c completed March 8, 2026, 3:38 p.m.
Created at: March 8, 2026, 3:02 p.m.