Triple

T6393093
Position Surface form Disambiguated ID Type / Status
Subject Greater Jakarta E143874 entity
Predicate hasUrbanSprawl P29003 FINISHED
Object extends into Banten Province 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: extends into Banten Province | Statement: [Greater Jakarta, hasUrbanSprawl, extends into Banten Province]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasUrbanSprawl
Context triple: [Greater Jakarta, hasUrbanSprawl, extends into Banten Province]
  • A. isUrbanizing
    Indicates a process in which an area or population becomes more urban in character, typically through increased development, infrastructure, and concentration of people and activities.
  • B. isUrbanized
    Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
  • C. hasUrbanGrowthCharacteristic chosen
    Indicates that an entity exhibits a particular quality, pattern, or feature related to urban growth or expansion.
  • D. hasSuburbanAreas
    Indicates that a place includes or is associated with surrounding residential suburban districts or neighborhoods.
  • E. hasSuburbanGrowth
    Indicates that an area or entity is experiencing or characterized by expansion or development typical of suburban environments.
  • 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_69c008db906c819096f3597d55d95432 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0687f5c6c81909c835329c996b311 completed March 22, 2026, 10:09 p.m.
PD Predicate disambiguation batch_69c060f25c088190b433f78553ff1d84 completed March 22, 2026, 9:36 p.m.
Created at: March 22, 2026, 4:34 p.m.