Triple

T20034204
Position Surface form Disambiguated ID Type / Status
Subject Universal Time 2 E497214 entity
Predicate correctionType P138454 FINISHED
Object seasonal variation correction 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: seasonal variation correction | Statement: [Universal Time 2, correctionType, seasonal variation correction]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: correctionType
Context triple: [Universal Time 2, correctionType, seasonal variation correction]
  • A. usesCorrectorType
    Indicates that one entity applies or employs a corrector of the specified type in performing an action or process.
  • B. requiresCorrection
    Indicates that something is identified as needing modification, adjustment, or fixing to correct an error or deficiency.
  • C. includesCorrectionsFor
    Indicates that one item contains modifications, fixes, or amendments that address errors or issues present in another item.
  • D. canBeCorrectedBy
    Indicates that something has the potential to be made accurate, fixed, or improved through the intervention or action of a specified agent or method.
  • E. canBeCorrectedTo
    Indicates that one entity can be modified or adjusted so that it becomes equivalent to or matches another entity.
  • 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_69da627278c88190babe4297a9df1236 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662e6a7e481908069c1de2b3f94e0 completed April 20, 2026, 5:31 p.m.
PD Predicate disambiguation batch_69e54ce752748190a0a1ffddd0372271 completed April 19, 2026, 9:45 p.m.
PDg Predicate description generation batch_69e54fc20888819083c9118a09d0d2dc completed April 19, 2026, 9:57 p.m.
Created at: April 11, 2026, 3:36 p.m.