Triple

T4080009
Position Surface form Disambiguated ID Type / Status
Subject Independent (football) E87453 entity
Predicate temporalVariation P44297 FINISHED
Object number of independent programs changes over time 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: number of independent programs changes over time | Statement: [Independent (football), temporalVariation, number of independent programs changes over time]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: temporalVariation
Context triple: [Independent (football), temporalVariation, number of independent programs changes over time]
  • A. temporalAspect
    Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
  • B. temporalEffect
    Indicates a relationship where one event, state, or action produces consequences or changes that occur at a later time.
  • C. timeDependence chosen
    Indicates that one entity’s state, value, or behavior is determined by or varies as a function of another entity over time.
  • D. flowVariation
    Indicates how the rate or pattern of flow (such as water, traffic, or data) changes over time or across different conditions.
  • E. temporalRelation
    Indicates a relationship that specifies how two events or states are positioned relative to each other in time (e.g., before, after, or overlapping).
  • 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_69aed9435cf48190ad1da737c962d19d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc5087b081909d6042bfe8d8a306 completed March 9, 2026, 4:58 p.m.
PD Predicate disambiguation batch_69aef9082c2081908474f082a49bebc8 completed March 9, 2026, 4:44 p.m.
Created at: March 9, 2026, 3:39 p.m.