Triple

T4696203
Position Surface form Disambiguated ID Type / Status
Subject Rafferty Law E104147 entity
Predicate familyName P18 FINISHED
Object Law E71463 NE 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 | Statement: [Rafferty Law, familyName, Law]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Law
Context triple: [Rafferty Law, familyName, Law]
  • A. Law chosen
    Law is the system of rules and principles recognized by a community or government as regulating the actions of its members and enforceable by legal institutions.
  • B. Law and Justice
    Law and Justice is a right-wing populist and national-conservative political party in Poland that has been one of the country’s dominant governing forces in the 21st century.
  • C. Laws
    Laws is one of Plato’s late philosophical dialogues, presenting a detailed exploration of legal theory, political organization, and the ideal constitution for a well-ordered city.
  • D. Recht
    Recht is a village and district within the municipality of Sankt Vith in the German-speaking region of eastern Belgium.
  • E. Law School
    The Law School at Marquette University is a professional graduate institution that educates students in legal theory and practice, preparing them for careers in law and related fields.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69bd43df91f481908e9add1b617b60ef completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63b2eb708190962f460063615f9a completed March 20, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69be03c3e6f48190b2f61de26192f5c4 completed March 21, 2026, 2:34 a.m.
Created at: March 20, 2026, 1:17 p.m.