Triple

T4466637
Position Surface form Disambiguated ID Type / Status
Subject France and Italy E98393 entity
Predicate shareClimateZones P56680 FINISHED
Object Mediterranean climate in coastal regions 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: Mediterranean climate in coastal regions | Statement: [France and Italy, shareClimateZones, Mediterranean climate in coastal regions]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: shareClimateZones
Context triple: [France and Italy, shareClimateZones, Mediterranean climate in coastal regions]
  • A. hasClimate
    Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
  • B. hasClimateContext
    Indicates that something is associated with, influenced by, or relevant to climate-related conditions, factors, or considerations.
  • C. climatologicalType
    Indicates the classification of a climate or weather pattern that characterizes a place, period, or condition.
  • D. nativeToClimate
    Indicates that an entity naturally originates from or is originally adapted to a specified climate or climatic region.
  • E. climaticChallenge
    Indicates a relationship where an entity faces, contributes to, or is affected by significant difficulties or stresses arising from climate or weather conditions.
  • F. None of above. chosen

Provenance (4 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_69b3454b4ae481908967426dd37284d6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b356fb69a0819099f0005779f4fcac completed March 13, 2026, 12:14 a.m.
PD Predicate disambiguation batch_69b3563bf4f8819081726cde3a34460b completed March 13, 2026, 12:11 a.m.
PDg Predicate description generation batch_69b356f9afc48190acb50c45a310e072 completed March 13, 2026, 12:14 a.m.
Created at: March 12, 2026, 11:34 p.m.