Triple

T31731435
Position Surface form Disambiguated ID Type / Status
Subject Kingsessing Library E809869 entity
Predicate hasComputersForPublicUse P204044 FINISHED
Object yes 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: yes | Statement: [Kingsessing Library, hasComputersForPublicUse, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasComputersForPublicUse
Context triple: [Kingsessing Library, hasComputersForPublicUse, yes]
  • A. hasPublicSpaces
    Indicates that an entity includes or provides areas that are accessible and usable by the general public.
  • B. isFreeOrPublic
    Indicates that the entity is available for use, access, or participation without cost or with unrestricted public access.
  • C. hasPartOpenToPublic
    Indicates that some portion or component of an entity is accessible for use or visitation by the general public.
  • D. hasSiteUse
    Indicates that a site is used or designated for a particular function, activity, or purpose.
  • E. hasPublicRooms
    Indicates that an entity possesses one or more rooms that are accessible or available for use by the general public.
  • F. None of above. chosen

Provenance (4 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_69f348e0e4908190a884582eca646fb7 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_6a0311c202408190be88a85337aacf11 completed May 12, 2026, 11:40 a.m.
PD Predicate disambiguation batch_6a0310b0c9c88190ab218d47d4f432ed completed May 12, 2026, 11:36 a.m.
PDg Predicate description generation batch_6a0311c145a08190ba7658db898ab7d6 completed May 12, 2026, 11:40 a.m.
Created at: April 30, 2026, 11:21 p.m.