Triple

T11294497
Position Surface form Disambiguated ID Type / Status
Subject Danish trade unions E267415 entity
Predicate useMechanism P8166 FINISHED
Object collective agreements 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: collective agreements | Statement: [Danish trade unions, useMechanism, collective agreements]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: useMechanism
Context triple: [Danish trade unions, useMechanism, collective agreements]
  • A. hasMechanism chosen
    Indicates that one entity operates, functions, or produces an effect through the specified mechanism or process.
  • B. definesMechanism
    Indicates that one entity specifies or explains the underlying process or mechanism by which another entity operates or occurs.
  • C. mentionsMechanism
    Indicates that one entity explicitly refers to or describes the mechanism, process, or causal pathway by which another entity operates or produces an effect.
  • D. interactionMechanism
    Indicates the process or means by which one entity affects, influences, or interacts with another.
  • E. createsMechanismFor
    Indicates that one entity brings about or establishes a means, process, or structure that enables or facilitates a particular function or outcome for another entity.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e98b149481909f432a6b9ef8bfbb completed April 9, 2026, 6:01 p.m.
PD Predicate disambiguation batch_69d787a6ca2c8190afdc24b61ccd3f8a completed April 9, 2026, 11:04 a.m.
Created at: April 8, 2026, 9:32 p.m.