Triple

T13597555
Position Surface form Disambiguated ID Type / Status
Subject Special Counsel investigation into Russian interference in the 2016 United States elections E324859 entity
Predicate timeSpanMonthsApproximate P9860 FINISHED
Object 22 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: 22 | Statement: [Special Counsel investigation into Russian interference in the 2016 United States elections, timeSpanMonthsApproximate, 22]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: timeSpanMonthsApproximate
Context triple: [Special Counsel investigation into Russian interference in the 2016 United States elections, timeSpanMonthsApproximate, 22]
  • A. operatingMonthsApproximate
    Indicates that the time period during which something operates is specified in approximate months rather than exact dates.
  • B. hasMonthCount chosen
    Indicates a relationship where an entity is associated with a specific number of months.
  • C. approximateTimeInYear
    Indicates that one time-related entity represents an estimated or non-exact point or interval within a given year for another entity.
  • D. hasAverageMonthLength
    Indicates that an entity is associated with a specified average length of a month, typically expressed in days.
  • E. dateApproximate
    Indicates that the associated date is not exact but estimated or approximate rather than precisely known.
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0590558819080ccc5874a650b1e completed April 12, 2026, 2:46 p.m.
PD Predicate disambiguation batch_69dbae18eaf48190809e8b365856cde9 completed April 12, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:49 p.m.