Triple

T3336670
Position Surface form Disambiguated ID Type / Status
Subject 2017 World Aquatics Championships E70154 entity
Predicate mascot P52 FINISHED
Object Lili
Lili is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
 E349663 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: Lili | Statement: [2017 World Aquatics Championships, mascot, Lili]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lili
Context triple: [2017 World Aquatics Championships, mascot, Lili]
  • A. Lili
    Lili is a 1953 musical fantasy film starring Leslie Caron as a naive orphan who joins a carnival and forms a touching bond with a puppeteer.
  • B. Lilia
    Lilia is a feminine given name, often considered a variant of Lily and associated with the elegance and symbolism of the lily flower.
  • C. Lillita
    Lillita is the birth name of Lita Grey, the American actress best known for her early silent film work and marriage to Charlie Chaplin.
  • D. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • E. Lillie
    Lillie is the given name of Lillie Hitchcock Coit, a famed 19th-century San Francisco socialite and patron associated with the city’s firefighting history.
  • 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: Lili
Triple: [2017 World Aquatics Championships, mascot, Lili]
Generated description
Lili is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lili
Target entity description: Lili is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
  • A. Lili
    Lili is a 1953 musical fantasy film starring Leslie Caron as a naive orphan who joins a carnival and forms a touching bond with a puppeteer.
  • B. Lilia
    Lilia is a feminine given name, often considered a variant of Lily and associated with the elegance and symbolism of the lily flower.
  • C. Lillita
    Lillita is the birth name of Lita Grey, the American actress best known for her early silent film work and marriage to Charlie Chaplin.
  • D. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • E. Lillie
    Lillie is the given name of Lillie Hitchcock Coit, a famed 19th-century San Francisco socialite and patron associated with the city’s firefighting history.
  • 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bad97481909359e914d44a1a74 completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a8ad1a8819081d7ad2a48e2c5b9 completed March 12, 2026, 7:56 p.m.
NEDg Description generation batch_69b31c393f20819098d5761372d6a980 completed March 12, 2026, 8:04 p.m.
NED2 Entity disambiguation (via description) batch_69b3206be2748190874560701dc1ed18 completed March 12, 2026, 8:22 p.m.
Created at: March 8, 2026, 3:12 p.m.