Triple

T3385062
Position Surface form Disambiguated ID Type / Status
Subject Quaker State E71279 entity
Predicate hasDemographicAssociation P7875 FINISHED
Object historic Quaker population in Pennsylvania 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: historic Quaker population in Pennsylvania | Statement: [Quaker State, hasDemographicAssociation, historic Quaker population in Pennsylvania]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDemographicAssociation
Context triple: [Quaker State, hasDemographicAssociation, historic Quaker population in Pennsylvania]
  • A. hasDemographic chosen
    Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
  • B. hasDemographicPattern
    Indicates that there is a characteristic distribution or trend of attributes (such as age, gender, income, or ethnicity) within a population or group.
  • C. demographicsDescriptor
    Indicates a descriptive attribute or classification that characterizes the demographic properties of an entity or group.
  • D. hasDemographicCenter
    Indicates that an entity has a primary geographic location where the majority or core concentration of its associated population or demographic group is found.
  • E. demographicCharacteristic
    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.
  • 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_69ad85a8fd9c819095ecedf838d2bf1b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb5ee5e188190912dcea494a12038 completed March 8, 2026, 5:46 p.m.
PD Predicate disambiguation batch_69ada434bae48190a77ea37f9274ad8f completed March 8, 2026, 4:30 p.m.
Created at: March 8, 2026, 3:14 p.m.