Triple

T4466619
Position Surface form Disambiguated ID Type / Status
Subject France and Italy E98393 entity
Predicate shareLegalSystemFamily P16986 FINISHED
Object civil 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: civil law | Statement: [France and Italy, shareLegalSystemFamily, civil law]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: shareLegalSystemFamily
Context triple: [France and Italy, shareLegalSystemFamily, civil law]
  • A. relatedLegalSystem chosen
    Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
  • B. 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.
  • C. legalSystemWorkedIn
    Indicates that a person carried out their professional legal activities within a particular legal system or jurisdiction.
  • D. separateLegalSystem
    Indicates that one entity maintains its own distinct and independent legal system from another entity.
  • E. legalSystemDepictedAs
    Indicates that one entity portrays, represents, or characterizes a legal system in a particular way or form.
  • 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_69b3454b4ae481908967426dd37284d6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b356fb69a0819099f0005779f4fcac completed March 13, 2026, 12:14 a.m.
PD Predicate disambiguation batch_69b3563bf4f8819081726cde3a34460b completed March 13, 2026, 12:11 a.m.
Created at: March 12, 2026, 11:34 p.m.