Triple

T6227256
Position Surface form Disambiguated ID Type / Status
Subject Bezirk Berlin E139264 entity
Predicate hadLegalSystem P605 FINISHED
Object law of the German Democratic Republic 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: law of the German Democratic Republic | Statement: [Bezirk Berlin, hadLegalSystem, law of the German Democratic Republic]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hadLegalSystem
Context triple: [Bezirk Berlin, hadLegalSystem, law of the German Democratic Republic]
  • A. legalSystem chosen
    Indicates the formal framework of laws, rules, and institutions that governs how legal matters are defined, interpreted, and enforced within a society or jurisdiction.
  • B. relatedLegalSystem
    Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
  • C. haveCivilLaw
    Indicates that an entity is subject to, governed by, or operates under a civil law legal system.
  • D. legalSystemDepictedAs
    Indicates that one entity portrays, represents, or characterizes a legal system in a particular way or form.
  • 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_69c008afd3148190b71e9eaa60420dd1 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062d686b88190a0e7e38ab52e2d4a completed March 22, 2026, 9:44 p.m.
PD Predicate disambiguation batch_69c055ffdf54819086d987d646e44ff5 completed March 22, 2026, 8:50 p.m.
Created at: March 22, 2026, 4:22 p.m.