Triple

T29589268
Position Surface form Disambiguated ID Type / Status
Subject French territorial reform of 2014 E754107 entity
Predicate changedNumberOfRegionsAfter P167981 FINISHED
Object 13 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: 13 | Statement: [French territorial reform of 2014, changedNumberOfRegionsAfter, 13]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: changedNumberOfRegionsAfter
Context triple: [French territorial reform of 2014, changedNumberOfRegionsAfter, 13]
  • A. changedNumberOfRegionsBefore
    Indicates that an entity previously had a different number of regions than it has at the referenced later point in time.
  • B. numberOfNewRegions
    Indicates the count of regions that have been newly created or added within a specified context or time frame.
  • C. changedNumberOf
    Indicates that the quantity of one entity has been altered by another entity or event.
  • D. numberOfRegions
    Indicates the total count of distinct regions associated with or contained within a given entity.
  • E. reorganisedRegion
    Indicates that a region has undergone a structural or administrative change, resulting in a new or altered regional configuration.
  • 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_69f0ef836ac88190bd809dc58b5ec907 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f66e5f7e30819094530abceabd5f43 completed May 2, 2026, 9:36 p.m.
PD Predicate disambiguation batch_69f66abfdaf08190a55f14c70be6fd4d completed May 2, 2026, 9:21 p.m.
PDg Predicate description generation batch_69f66d75a8788190aa9ca2c977429045 completed May 2, 2026, 9:32 p.m.
Created at: April 28, 2026, 6:13 p.m.