Triple

T728615
Position Surface form Disambiguated ID Type / Status
Subject Iztapalapa E14782 entity
Predicate urbanization P17246 FINISHED
Object highly urbanized area 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: highly urbanized area | Statement: [Iztapalapa, urbanization, highly urbanized area]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: urbanization
Context triple: [Iztapalapa, urbanization, highly urbanized area]
  • A. urbanizationLevel
    Indicates the degree to which an area or population is characterized by urban development, infrastructure, and density of human settlement.
  • B. urbanDevelopment
    Indicates the process or activities through which urban areas are planned, expanded, or transformed, including changes to infrastructure, land use, and the built environment.
  • C. isUrbanized chosen
    Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
  • D. urbanAreaType
    Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
  • E. urbanDevelopmentType
    Indicates the specific category or nature of urban development associated with or applied to an entity (e.g., residential, commercial, mixed-use).
  • 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_69a4934c753c81909b309027e48b9b3a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a64adf2c81908e48090be35dd9d9 completed March 1, 2026, 8:49 p.m.
PD Predicate disambiguation batch_69a4a4f839608190878a60eb7a044ed9 completed March 1, 2026, 8:43 p.m.
Created at: March 1, 2026, 7:37 p.m.