Triple

T31309967
Position Surface form Disambiguated ID Type / Status
Subject Oslo municipality and Bærum municipality E798434 entity
Predicate shareLaborMarket P43644 FINISHED
Object true 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: true | Statement: [Oslo municipality and Bærum municipality, shareLaborMarket, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: shareLaborMarket
Context triple: [Oslo municipality and Bærum municipality, shareLaborMarket, true]
  • A. sharesLaborMarketWith chosen
    Indicates that two entities operate within the same or substantially overlapping labor market, drawing from and competing for a similar pool of workers.
  • B. laborMarket
    Indicates the relationship between workers seeking jobs and employers offering positions, including how wages, employment levels, and working conditions are determined through their interaction.
  • C. laborMarketUsage
    Indicates how an entity utilizes, participates in, or depends on the labor market for work, hiring, or employment-related activities.
  • D. laborMarketTest
    Indicates that an employer has attempted to recruit suitable local or domestic workers before offering the position to a foreign or non-local candidate.
  • E. peakEmployment
    Indicates that an entity has reached its highest level of employment or workforce size during a specified period.
  • 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_69f224e1932c81908fef14f7b03a10b7 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69fed6da0390819096b88ef4714b144e completed May 9, 2026, 6:40 a.m.
PD Predicate disambiguation batch_69fed53517d081909966f31707625f1a completed May 9, 2026, 6:33 a.m.
Created at: April 29, 2026, 9:15 p.m.