Triple

T11234287
Position Surface form Disambiguated ID Type / Status
Subject new towns program of Egypt E265902 entity
Predicate populationPolicyRole P14446 FINISHED
Object redistribution of population 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: redistribution of population | Statement: [new towns program of Egypt, populationPolicyRole, redistribution of population]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: populationPolicyRole
Context triple: [new towns program of Egypt, populationPolicyRole, redistribution of population]
  • A. populationRole
    Indicates the role or function that an entity has within a population or demographic context.
  • B. ethnicRole
    Indicates a role, function, or social position that is specifically associated with or defined by an entity’s ethnicity.
  • C. demographicPolicy chosen
    Indicates a relationship where an authority or organization establishes or applies rules and measures intended to influence the size, structure, or composition of a population.
  • D. urbanPolicyRole
    Indicates a role or responsibility that an entity has in shaping, implementing, or influencing urban policy.
  • E. countryNationalRole
    Indicates the official function, position, or responsibility that an entity holds at the national level within a specific country.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e903b8ec81909f9c89776d35c650 completed April 9, 2026, 5:59 p.m.
PD Predicate disambiguation batch_69d75cfdf7a88190aae21572e57ef208 completed April 9, 2026, 8:02 a.m.
Created at: April 8, 2026, 9:30 p.m.