Triple

T16930215
Position Surface form Disambiguated ID Type / Status
Subject Geneva, New York E410684 entity
Predicate hasHigherEducationType P124790 FINISHED
Object liberal arts colleges 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: liberal arts colleges | Statement: [Geneva, New York, hasHigherEducationType, liberal arts colleges]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasHigherEducationType
Context triple: [Geneva, New York, hasHigherEducationType, liberal arts colleges]
  • A. hasHigherEducationHistory
    Indicates that an entity has a record of having pursued or completed higher education studies in the past.
  • B. hasHigherEducationAccess
    Indicates that one entity has access to higher education opportunities or institutions relative to another entity or context.
  • C. hasEducationIn
    Indicates that an entity has received education, training, or formal study in a specified field, subject, or discipline.
  • D. hasHighestDegree
    Indicates that one entity possesses the highest academic degree attained by another entity.
  • E. hasCollegeType
    Indicates that a college or educational institution is classified as having a specific type or category (e.g., public, private, community, technical).
  • 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_69d886c886688190967be07322597ac9 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cf248c6c81908fbf4d49e5381f08 completed April 18, 2026, 6:36 p.m.
PD Predicate disambiguation batch_69e32b982f548190b08414d55810de19 completed April 18, 2026, 6:58 a.m.
PDg Predicate description generation batch_69e32d7aae948190bc238d765795688c completed April 18, 2026, 7:06 a.m.
Created at: April 10, 2026, 5:30 a.m.