Triple

T52406
Position Surface form Disambiguated ID Type / Status
Subject Yale University campus E1028 entity
Predicate urbanSetting P749 FINISHED
Object urban campus 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: urban campus | Statement: [Yale University campus, urbanSetting, urban campus]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: urbanSetting
Context triple: [Yale University campus, urbanSetting, urban campus]
  • A. urbanAreaType chosen
    Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
  • B. hasUrbanFeature
    Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
  • C. neighborhood
    Indicates that one entity is located in close spatial proximity to another, typically within the same local area or district.
  • D. partOfMetropolitanArea
    Indicates that one place is included within and belongs to the larger metropolitan area of another place.
  • E. servesAsFocusCityFor
    Indicates that a city functions as a primary or designated focus city for an airline, organization, or transportation network, typically hosting significant but not hub-level operations or activities.
  • 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_69a2480baefc81909951b14058479aa2 completed Feb. 28, 2026, 1:42 a.m.
NER Named-entity recognition batch_69a24c709c248190bcd442c8d508e48c completed Feb. 28, 2026, 2:01 a.m.
PD Predicate disambiguation batch_69a24ac3c8dc819099849023bdaa35a9 completed Feb. 28, 2026, 1:54 a.m.
Created at: Feb. 28, 2026, 1:47 a.m.