Triple

T31737166
Position Surface form Disambiguated ID Type / Status
Subject Rivière aux Feuilles E810032 entity
Predicate hasHumanSettlementCharacteristic P172974 FINISHED
Object very low population density 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: very low population density | Statement: [Rivière aux Feuilles, hasHumanSettlementCharacteristic, very low population density]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasHumanSettlementCharacteristic
Context triple: [Rivière aux Feuilles, hasHumanSettlementCharacteristic, very low population density]
  • A. hasHumanSettlement
    Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
  • B. hadSettlementFeature
    Indicates that a settlement possessed or contained a particular physical or infrastructural feature.
  • C. hasHumanSettlementDependency
    Indicates that one human settlement relies on or is dependent upon another settlement for certain functions, resources, or services.
  • D. hasTraditionalSettlementType
    Indicates that an entity is associated with a specific traditional or historically established type of human settlement (e.g., village, town, hamlet).
  • E. hasCityStatusSettlement
    Indicates that a settlement possesses official recognition or designation as a city.
  • 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_69f348e0e4908190a884582eca646fb7 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6b2d9aad88190a445f8f591cb19fc completed May 3, 2026, 2:28 a.m.
PD Predicate disambiguation batch_69f6b14faf608190a25b977c0740729c completed May 3, 2026, 2:22 a.m.
PDg Predicate description generation batch_69f6b21da77081908c5c015c4606d344 completed May 3, 2026, 2:25 a.m.
Created at: April 30, 2026, 11:23 p.m.