Triple

T21108812
Position Surface form Disambiguated ID Type / Status
Subject Train to Pakistan E520122 entity
Predicate frequentlyStudiedIn P46827 FINISHED
Object university literature courses 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: university literature courses | Statement: [Train to Pakistan, frequentlyStudiedIn, university literature courses]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: frequentlyStudiedIn
Context triple: [Train to Pakistan, frequentlyStudiedIn, university literature courses]
  • A. widelyStudiedIn chosen
    Indicates that something has been extensively researched, analyzed, or examined within a particular field, domain, or context.
  • B. oftenStudiedBetween
    Indicates that something is frequently examined, researched, or analyzed in relation to two or more entities.
  • C. oftenStudiedWith
    Indicates that two subjects or topics are frequently studied together, typically within the same context, course, or learning activity.
  • D. alsoStudied
    Indicates that an entity pursued additional studies in another subject, field, or institution besides a primary one.
  • E. studiedBy
    Indicates that a subject (such as a field, topic, or object) is examined, researched, or learned by an agent (such as a person or group).
  • 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_69e0b509a318819092fbbcb21d1fe603 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e720ffa998819082db225363ac3b23 completed April 21, 2026, 7:02 a.m.
PD Predicate disambiguation batch_69e5dbff56848190a03b350a9305c612 completed April 20, 2026, 7:55 a.m.
Created at: April 16, 2026, 2:54 p.m.