Triple

T10002565
Position Surface form Disambiguated ID Type / Status
Subject Oughtrington Brook E197361 entity
Predicate hasLandscapeImpact P89454 FINISHED
Object shapes local topography in parts of Lymm 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: shapes local topography in parts of Lymm | Statement: [Oughtrington Brook, hasLandscapeImpact, shapes local topography in parts of Lymm]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLandscapeImpact
Context triple: [Oughtrington Brook, hasLandscapeImpact, shapes local topography in parts of Lymm]
  • A. hasLandscapeFeatures
    Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
  • B. hasLandscapeDesignInfluence
    Indicates that one entity has influenced or shaped the landscape design style, principles, or features of another entity.
  • C. hasEnvironmentalImpactOn
    Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
  • D. hasLocalImpact chosen
    Indicates that an entity produces effects or consequences within a specific local area or community.
  • E. hasImpactFocus
    Indicates that an entity is primarily concerned with or directed toward a particular type or area of impact.
  • 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_69ca82f3b61c81908ecc2c1c96dbc2e4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdcc9078788190a4e75dd7ff830c63 completed April 2, 2026, 1:55 a.m.
PD Predicate disambiguation batch_69cd1da2cf9081908a6c0eb5247d0bc2 completed April 1, 2026, 1:29 p.m.
Created at: March 30, 2026, 8:51 p.m.