Triple

T7828683
Position Surface form Disambiguated ID Type / Status
Subject Chicago Scholars E181309 entity
Predicate targetPopulationCharacteristic P17586 FINISHED
Object low-income students 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: low-income students | Statement: [Chicago Scholars, targetPopulationCharacteristic, low-income students]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: targetPopulationCharacteristic
Context triple: [Chicago Scholars, targetPopulationCharacteristic, low-income students]
  • A. demographicsCharacteristic
    Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
  • B. targetedPopulation chosen
    Indicates the group of individuals or entities that an action, intervention, or effect is specifically directed toward.
  • C. 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.
  • D. membershipCharacteristic
    Indicates that an entity possesses a specific attribute or quality by virtue of its membership in a particular group or category.
  • E. laborForceCharacteristic
    Indicates a relationship where an entity is described or classified by a specific attribute or status related to its participation in the labor force.
  • 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_69ca8282ccec819083c48efb72d21cf9 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb04aaed1881908e1da129a43ef9c7 completed March 30, 2026, 11:18 p.m.
PD Predicate disambiguation batch_69cae91ae008819098e56bbe51143b31 completed March 30, 2026, 9:20 p.m.
Created at: March 30, 2026, 4:43 p.m.