Triple

T716714
Position Surface form Disambiguated ID Type / Status
Subject Antalya E14330 entity
Predicate secondaryEconomicSector P71 FINISHED
Object agriculture 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: agriculture | Statement: [Antalya, secondaryEconomicSector, agriculture]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: secondaryEconomicSector
Context triple: [Antalya, secondaryEconomicSector, agriculture]
  • A. sector chosen
    Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
  • B. economicSectorSourceOfWealth
    Indicates that a particular economic sector is the primary source from which an entity derives its wealth or income.
  • C. economicSectorIssue
    Indicates that there is a problem, challenge, or concern affecting a particular economic sector.
  • D. economicClassification
    Indicates how an entity is categorized based on its economic characteristics, status, or role within an economic system.
  • E. economicUse
    Indicates that one entity utilizes another for economic purposes, such as production, trade, revenue generation, or cost-saving activities.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a57649dc8190bfdee2f9c0c90415 completed March 1, 2026, 8:45 p.m.
PD Predicate disambiguation batch_69a4a4f38898819089d79bad4f4ff2d2 completed March 1, 2026, 8:43 p.m.
Created at: March 1, 2026, 7:37 p.m.