Triple

T19176057
Position Surface form Disambiguated ID Type / Status
Subject Central Place development E469438 entity
Predicate skylineImpact P102013 FINISHED
Object significant visual impact on Arlington skyline 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: significant visual impact on Arlington skyline | Statement: [Central Place development, skylineImpact, significant visual impact on Arlington skyline]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: skylineImpact
Context triple: [Central Place development, skylineImpact, significant visual impact on Arlington skyline]
  • A. skylineType
    Indicates the general visual or structural character of a skyline, such as its dominant form, density, or profile.
  • B. impactBuilding
    Indicates that one entity physically collides with or strikes a building, causing an impact event.
  • C. 都市景観への影響 chosen
    Indicates the effect or impact that something has on the appearance, structure, or overall quality of the urban landscape.
  • D. partOfSkylineOf
    Indicates that one entity is a visible component or feature contributing to the overall skyline profile of another entity, typically a city or urban area.
  • E. impactBorough
    Indicates a relationship where an event, action, or condition has an effect on, or causes consequences for, a specific borough.
  • 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f6181f0c8190b344072db0b7abbb completed April 20, 2026, 9:47 a.m.
PD Predicate disambiguation batch_69e4b9bb158481909478ca2e06f3ba39 completed April 19, 2026, 11:17 a.m.
Created at: April 10, 2026, 12:06 p.m.