Triple

T265335
Position Surface form Disambiguated ID Type / Status
Subject Class V: Social Sciences, Law and Economics E5709 entity
Predicate belongsToSector P2193 FINISHED
Object higher education and research 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: higher education and research | Statement: [Class V: Social Sciences, Law and Economics, belongsToSector, higher education and research]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: belongsToSector
Context triple: [Class V: Social Sciences, Law and Economics, belongsToSector, higher education and research]
  • A. sectorServed chosen
    Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
  • B. operatesInSegment
    Indicates that an entity conducts its activities or provides its services within a specified market or operational segment.
  • C. hasAffiliationType
    Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
  • D. hasBusinessDivision
    Indicates that an organization includes or is composed of a specific business division as a subordinate unit.
  • E. isAssociatedWith
    Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
  • 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_69a2587daeb081909591b9d30f80a271 completed Feb. 28, 2026, 2:52 a.m.
NER Named-entity recognition batch_69a25d8f9bbc8190a13841e4de093a66 completed Feb. 28, 2026, 3:14 a.m.
PD Predicate disambiguation batch_69a25b6f60b081908fc6467800a8849e completed Feb. 28, 2026, 3:05 a.m.
Created at: Feb. 28, 2026, 2:56 a.m.