Triple

T15581594
Position Surface form Disambiguated ID Type / Status
Subject Ancien Régime in Paris E374511 entity
Predicate hasDemographyFeature P2501 FINISHED
Object high 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: high population density | Statement: [Ancien Régime in Paris, hasDemographyFeature, high population density]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDemographyFeature
Context triple: [Ancien Régime in Paris, hasDemographyFeature, high population density]
  • A. hasDemographic
    Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
  • B. demographicCharacteristic chosen
    Indicates that one entity specifies or describes a demographic attribute or feature (such as age, gender, ethnicity, or similar population-related trait) of another entity.
  • C. demographicsCharacteristic
    Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
  • D. hasDemographicPattern
    Indicates that there is a characteristic distribution or trend of attributes (such as age, gender, income, or ethnicity) within a population or group.
  • E. hasDemographicPresenceIn
    Indicates that a particular demographic group exists or is represented within a specified geographic area or population context.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e45ee3c8190a6aee06a5805ca39 completed April 16, 2026, 2:49 a.m.
PD Predicate disambiguation batch_69deda817e9881909b0c66fc9056f7d5 completed April 15, 2026, 12:23 a.m.
Created at: April 10, 2026, 4:11 a.m.