Triple

T4551530
Position Surface form Disambiguated ID Type / Status
Subject Portugal and Spain E110173 entity
Predicate haveDistinctLegalSystems P2988 FINISHED
Object true 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: true | Statement: [Portugal and Spain, haveDistinctLegalSystems, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: haveDistinctLegalSystems
Context triple: [Portugal and Spain, haveDistinctLegalSystems, true]
  • A. separateLegalSystem chosen
    Indicates that one entity maintains its own distinct and independent legal system from another entity.
  • B. relatedLegalSystem
    Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
  • C. countryJurisdiction
    Indicates that one country has legal authority, control, or governing power over a specified territory, entity, or matter.
  • D. hasLegalAutonomyFrom
    Indicates that one entity possesses independent legal authority or decision-making power that is not subject to control or oversight by another specified entity.
  • E. legalSystem
    Indicates the formal framework of laws, rules, and institutions that governs how legal matters are defined, interpreted, and enforced within a society or jurisdiction.
  • 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_69bd4412524c8190be5bcc9ddee91848 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57f7b9748190af29d02fc77b02e0 completed March 20, 2026, 2:21 p.m.
PD Predicate disambiguation batch_69bd5223423c81908317351b58cff5f5 completed March 20, 2026, 1:56 p.m.
Created at: March 20, 2026, 1:05 p.m.