Triple

T17452657
Position Surface form Disambiguated ID Type / Status
Subject Multimedia Fountain Wrocław E424950 entity
Predicate hasNumberOfSpotlights P37175 FINISHED
Object about 800 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: about 800 | Statement: [Multimedia Fountain Wrocław, hasNumberOfSpotlights, about 800]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSpotlights
Context triple: [Multimedia Fountain Wrocław, hasNumberOfSpotlights, about 800]
  • A. hasNumberOfMainLights
    Indicates the relationship that specifies how many primary or main lights are associated with an entity.
  • B. numberOfLights chosen
    Indicates the quantity of lights associated with or present on a given entity.
  • C. hasLighting
    Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
  • D. hasNumberOfShamashLights
    Indicates the relationship specifying how many Shamash (helper) lights are present or associated with an object or setting.
  • E. hasLanternLightSource
    Indicates that an entity uses a lantern as its source of light.
  • 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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4513faa0c8190961cf504c459bf34 completed April 19, 2026, 3:51 a.m.
PD Predicate disambiguation batch_69e3b4f0e3fc819094e466b74622c956 completed April 18, 2026, 4:44 p.m.
Created at: April 10, 2026, 5:47 a.m.