Triple

T4777020
Position Surface form Disambiguated ID Type / Status
Subject Bailey E106075 entity
Predicate Garnet BaileyRole P59255 FINISHED
Object former Los Angeles Kings director of pro scouting 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: former Los Angeles Kings director of pro scouting | Statement: [Bailey, Garnet BaileyRole, former Los Angeles Kings director of pro scouting]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: Garnet BaileyRole
Context triple: [Bailey, Garnet BaileyRole, former Los Angeles Kings director of pro scouting]
  • A. Lincoln Lewis
    Indicates a relationship or association involving the entity or name "Lincoln Lewis," such as authorship, participation, or attribution in a given context.
  • B. Michael CurryTitle
    Indicates that an entity holds the specific title or position associated with Michael Curry.
  • C. protagonistFullName
    Indicates that the subject entity is the full, proper name (including given and family names) of the story’s main protagonist.
  • D. Dan HartRole
    Indicates that Dan Hart holds or performs a specific role, position, or function in relation to another entity or context.
  • E. Ron Harper
    Indicates a relationship or action involving Ron Harper, such as participation, association, or attribution connected to this individual.
  • 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_69bd43f3074c8190937e7b0a457fe9f1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd69237f80819090713ed62653fb75 completed March 20, 2026, 3:34 p.m.
PD Predicate disambiguation batch_69bd622be1388190ab5511b589c878c0 completed March 20, 2026, 3:05 p.m.
PDg Predicate description generation batch_69bd6922407481908565ed0b1dac2b30 completed March 20, 2026, 3:34 p.m.
Created at: March 20, 2026, 1:21 p.m.