Triple

T11838928
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Law, CUHK E281594 entity
Predicate legalSystemFocus P605 FINISHED
Object common 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: common law | Statement: [Faculty of Law, CUHK, legalSystemFocus, common law]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: legalSystemFocus
Context triple: [Faculty of Law, CUHK, legalSystemFocus, common law]
  • 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. legalSystemDepictedAs
    Indicates that one entity portrays, represents, or characterizes a legal system in a particular way or form.
  • C. legalSystemSpecialization
    Indicates that a legal system is specialized or tailored to address a particular domain, issue, or type of case within the broader legal framework.
  • D. legalSystemWorkedIn
    Indicates that a person carried out their professional legal activities within a particular legal system or jurisdiction.
  • E. relatedLegalSystem
    Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
  • 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_69d6ab276f8c8190b1966a0ef11349ac completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a63106b48190917817ec40d21a49 completed April 10, 2026, 7:26 a.m.
PD Predicate disambiguation batch_69d8a254a57481908a1e6ad97919c416 completed April 10, 2026, 7:10 a.m.
Created at: April 8, 2026, 9:43 p.m.