Triple

T7946785
Position Surface form Disambiguated ID Type / Status
Subject King Zhuang of Chu E184516 entity
Predicate associatedWithAnecdote P79971 FINISHED
Object “three years without state affairs” story 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: “three years without state affairs” story | Statement: [King Zhuang of Chu, associatedWithAnecdote, “three years without state affairs” story]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithAnecdote
Context triple: [King Zhuang of Chu, associatedWithAnecdote, “three years without state affairs” story]
  • A. associatedWithUrbanLegend
    Indicates a relationship where something is connected to, derived from, or commonly regarded as part of an urban legend.
  • B. relatedProverb
    Indicates that one entity is a proverb that is thematically or conceptually related to another entity.
  • C. notablyAssociatedWith
    Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
  • D. notableFact
    Indicates that there exists a particularly significant or noteworthy fact or piece of information associated with the subject.
  • E. notableGag
    Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
  • 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_69ca8291c2008190b1b8832c87814bcf completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b29a570819091a2ac185a8d57c4 completed March 31, 2026, 3:10 a.m.
PD Predicate disambiguation batch_69cae93526d081909303265bf60419fd completed March 30, 2026, 9:20 p.m.
PDg Predicate description generation batch_69caf788db1c8190839523e7777961d6 completed March 30, 2026, 10:22 p.m.
Created at: March 30, 2026, 5:09 p.m.