Triple

T36965669
Position Surface form Disambiguated ID Type / Status
Subject Miss World USA 1972 E914420 entity
Predicate successorPageant P202582 FINISHED
Object Miss World USA 1973
Miss World USA 1973 was the national beauty pageant held in the United States in 1973 to select the country’s representative for the Miss World competition.
 E2206765 NE FINISHED

How this triple was built (3 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: Miss World USA 1973 | Statement: [Miss World USA 1972, successorPageant, Miss World USA 1973]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Miss World USA 1973
Triple: [Miss World USA 1972, successorPageant, Miss World USA 1973]
Generated description
Miss World USA 1973 was the national beauty pageant held in the United States in 1973 to select the country’s representative for the Miss World competition.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: successorPageant
Context triple: [Miss World USA 1972, successorPageant, Miss World USA 1973]
  • A. successorAsQueen
    Indicates that one entity became queen directly after another, inheriting the queenship as her successor.
  • B. successorAsPrincessRoyal
    Indicates that one person becomes the next holder of the title "Princess Royal" after another person.
  • C. successorAsSecondLady
    Indicates that one person became the next Second Lady, directly following another in that role.
  • D. successorAsPrincipalQueen
    Indicates that one individual becomes the next principal queen, directly succeeding another in that primary royal consort role.
  • E. successorPalace
    Indicates that one palace directly follows and replaces another in a succession or sequence.
  • F. None of above. chosen

Provenance (7 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_69f76e8c498c8190b2842db80aea8b3b completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_6a009a0e1fa481909ed881012009b268 completed May 10, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e2c42186081909abbd5f5fadf94d7 completed June 26, 2026, 7:37 a.m.
NEDg Description generation batch_6a3e2ce08a40819081db007321d0b279 completed June 26, 2026, 7:40 a.m.
NED2 Entity disambiguation (via description) batch_6a3e458016e881909cef925bc1bad341 completed June 26, 2026, 9:25 a.m.
PD Predicate disambiguation batch_6a0092e9fcb08190a966d720684f25ec completed May 10, 2026, 2:15 p.m.
PDg Predicate description generation batch_6a009a0d44b481908285ee39b64cb466 completed May 10, 2026, 2:45 p.m.
Created at: May 3, 2026, 4:14 p.m.