Triple

T1220777
Position Surface form Disambiguated ID Type / Status
Subject Rob Manfred E26216 entity
Predicate legalBackground P25968 FINISHED
Object labor and employment 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: labor and employment law | Statement: [Rob Manfred, legalBackground, labor and employment law]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: legalBackground
Context triple: [Rob Manfred, legalBackground, labor and employment law]
  • A. legalContext
    Indicates that the relationship or action occurs within, is shaped by, or is relevant to a specific legal framework, proceeding, or set of legal norms.
  • B. legalRepresentation
    Indicates that one entity formally acts on behalf of another in legal matters, such as providing counsel, advocacy, or defense within a legal system.
  • C. legalSubject
    Indicates that an entity is the bearer of legal rights, duties, or responsibilities within a legal relationship or context.
  • D. legalDoctrine
    Indicates that one legal principle, rule, or theory is being applied, referenced, or relied upon as an authoritative basis for interpreting or deciding a legal issue.
  • E. lawJournal
    Indicates a relationship where a work is published in, associated with, or appears within a specific law journal.
  • F. None of above. chosen

Provenance (4 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_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be1ead088190bf44dc6ab1edf18b completed March 1, 2026, 10:30 p.m.
PD Predicate disambiguation batch_69a4bb644af08190ba25905f20adb01a completed March 1, 2026, 10:19 p.m.
PDg Predicate description generation batch_69a4bd3140688190ac6e24de157fd61e completed March 1, 2026, 10:26 p.m.
Created at: March 1, 2026, 7:46 p.m.