Triple

T20317114
Position Surface form Disambiguated ID Type / Status
Subject nSP E510406 entity
Predicate appliesInLegalSystem P131132 FINISHED
Object English law 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: English law | Statement: [nSP, appliesInLegalSystem, English law]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: appliesInLegalSystem
Context triple: [nSP, appliesInLegalSystem, English law]
  • A. usedLegalSystemOf chosen
    Indicates that one entity applied, followed, or operated under the legal system or body of laws belonging to another entity.
  • B. countryOfLegalSystem
    Indicates the relationship between a legal system and the country in which that legal system is officially established or applied.
  • C. relatedLegalSystem
    Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
  • D. legalSystemRegion
    Indicates the geographic or jurisdictional region within which a particular legal system is applicable or in force.
  • E. partOfLegalSystem
    Indicates that something belongs to, is included within, or functions as a component of a particular legal system.
  • 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_69e0b4c7491c8190961113c4283b10b0 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e67788ca3c8190a3496fd54a5870d6 completed April 20, 2026, 6:59 p.m.
PD Predicate disambiguation batch_69e55b21b09081909e46691b6f45a07f completed April 19, 2026, 10:45 p.m.
Created at: April 16, 2026, 11:19 a.m.