Triple

T9326883
Position Surface form Disambiguated ID Type / Status
Subject John "Lucky" Garnett E224409 entity
Predicate nickname P55 FINISHED
Object Lucky
Lucky is the nickname of John "Lucky" Garnett, likely highlighting a reputation for good fortune or narrow escapes.
 E792461 NE FINISHED

How this triple was built (4 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: Lucky | Statement: [John "Lucky" Garnett, nickname, Lucky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lucky
Context triple: [John "Lucky" Garnett, nickname, Lucky]
  • A. Lucky
    "Lucky" is a popular duet by American singers Colbie Caillat and Jason Mraz, known for its mellow acoustic pop style and romantic lyrics.
  • B. Lucky
    Lucky is a tormented, subservient figure in Samuel Beckett’s play "Waiting for Godot," known for his near-muteness and one explosive, chaotic monologue that reflects the play’s themes of absurdity and existential despair.
  • C. Lucky
    Lucky is a contemplative 2017 independent film starring Harry Dean Stanton as a nonagenarian atheist confronting mortality in a small desert town.
  • D. Lucky
    Lucky is a bestselling novel by Jackie Collins that follows the glamorous, ruthless world of Lucky Santangelo in the high-stakes realms of power, sex, and crime.
  • E. Lucky
    "Lucky" is a popular Afrobeats/hip-hop song by Ghanaian rapper Sarkodie, known for its smooth blend of rap and melodic vocals.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Lucky
Triple: [John "Lucky" Garnett, nickname, Lucky]
Generated description
Lucky is the nickname of John "Lucky" Garnett, likely highlighting a reputation for good fortune or narrow escapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lucky
Target entity description: Lucky is the nickname of John "Lucky" Garnett, likely highlighting a reputation for good fortune or narrow escapes.
  • A. Lucky
    "Lucky" is a popular Afrobeats/hip-hop song by Ghanaian rapper Sarkodie, known for its smooth blend of rap and melodic vocals.
  • B. Lucky
    Lucky is the protagonist of the 1993 film "Poetic Justice," portrayed by Tupac Shakur as a sensitive and complex mail carrier navigating love, grief, and self-discovery.
  • C. Lucky
    "Lucky" is a popular duet by American singers Colbie Caillat and Jason Mraz, known for its mellow acoustic pop style and romantic lyrics.
  • D. Lucky
    Lucky is a regional supermarket chain brand in the United States known for its neighborhood grocery stores and value-focused offerings.
  • E. Lucky
    Lucky is a bestselling novel by Jackie Collins that follows the glamorous, ruthless world of Lucky Santangelo in the high-stakes realms of power, sex, and crime.
  • F. None of above. chosen

Provenance (5 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_69ca8427a0c08190b749831d5ea98f02 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd36f88e988190bb896a3d7c3c723c completed April 1, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e3c30ba88190b192621928136b87 completed April 4, 2026, 10:11 a.m.
NEDg Description generation batch_69d0e502b68081909a9f9476421ba9b5 completed April 4, 2026, 10:16 a.m.
NED2 Entity disambiguation (via description) batch_69d0e5af7360819096c6295de0ce5f32 completed April 4, 2026, 10:19 a.m.
Created at: March 30, 2026, 7:39 p.m.