Triple

T32818633
Position Surface form Disambiguated ID Type / Status
Subject Red Line (Washington Metro) stations E839370 entity
Predicate haveLighting P1280 FINISHED
Object artificial lighting 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: artificial lighting | Statement: [Red Line (Washington Metro) stations, haveLighting, artificial lighting]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: haveLighting
Context triple: [Red Line (Washington Metro) stations, haveLighting, artificial lighting]
  • A. hasLighting chosen
    Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
  • B. hasLightingEffect
    Indicates that one entity applies, produces, or is associated with a particular lighting effect on another entity or environment.
  • C. usesLightingFor
    Indicates that one entity employs or relies on a particular lighting setup, technology, or condition to achieve a purpose or perform an action.
  • D. lightingRequirement
    Indicates the level or type of light that is needed for something to function, grow, or be used properly.
  • E. hasLightingPolicy
    Indicates that there is a defined policy or set of rules governing how lighting is used, managed, or controlled for the related entity.
  • 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_69f3493df9008190a8f5d843dcd77704 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6ce6d659881909ddcec1d2966e020 completed May 3, 2026, 4:26 a.m.
PD Predicate disambiguation batch_69f6cc1667a48190b42684f6ec22dae9 completed May 3, 2026, 4:16 a.m.
Created at: May 1, 2026, 1:15 a.m.