Triple

T17219255
Position Surface form Disambiguated ID Type / Status
Subject Cosmicomics E417930 entity
Predicate hasStory P11859 FINISHED
Object How Much Shall We Bet
"How Much Shall We Bet" is a short story by Italo Calvino from his collection *Cosmicomics*, blending speculative cosmology with playful, philosophical fiction.
E1257707 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: How Much Shall We Bet | Statement: [Cosmicomics, hasStory, How Much Shall We Bet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: How Much Shall We Bet
Context triple: [Cosmicomics, hasStory, How Much Shall We Bet]
  • A. I Bet
    "I Bet" is an R&B song by American singer Ciara, released in 2015 and known for its emotionally charged lyrics about heartbreak and empowerment.
  • B. I Bet
    "I Bet" is a song by the American dream pop duo Beach House, known for its lush, atmospheric sound and introspective mood.
  • C. I Bet
    "I Bet" is a song released as a single by the artist Jackie.
  • D. The Odds
    The Odds is a novel by American author Stewart O'Nan that follows a middle-aged couple on the brink of divorce who take a final, desperate trip to Niagara Falls in hopes of salvaging both their marriage and finances.
  • E. The Big Gamble
    The Big Gamble is a 1961 adventure-comedy film about two men undertaking a perilous trucking venture in Africa.
  • 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: How Much Shall We Bet
Triple: [Cosmicomics, hasStory, How Much Shall We Bet]
Generated description
"How Much Shall We Bet" is a short story by Italo Calvino from his collection *Cosmicomics*, blending speculative cosmology with playful, philosophical fiction.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: How Much Shall We Bet
Target entity description: "How Much Shall We Bet" is a short story by Italo Calvino from his collection *Cosmicomics*, blending speculative cosmology with playful, philosophical fiction.
  • A. I Bet
    "I Bet" is an R&B song by American singer Ciara, released in 2015 and known for its emotionally charged lyrics about heartbreak and empowerment.
  • B. I Bet
    "I Bet" is a song by the American dream pop duo Beach House, known for its lush, atmospheric sound and introspective mood.
  • C. I Bet
    "I Bet" is a song released as a single by the artist Jackie.
  • D. The Odds
    The Odds is a novel by American author Stewart O'Nan that follows a middle-aged couple on the brink of divorce who take a final, desperate trip to Niagara Falls in hopes of salvaging both their marriage and finances.
  • E. The Big Gamble
    The Big Gamble is a 1961 adventure-comedy film about two men undertaking a perilous trucking venture in Africa.
  • 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_69d886d779488190b131369541c04e7d completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42ddc3cb88190a67e35164d710d9d completed April 19, 2026, 1:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01675553b88190a04987b0de62cb15 completed May 11, 2026, 5:21 a.m.
NEDg Description generation batch_6a0169e5f7e881909cb3fe35935d888d completed May 11, 2026, 5:32 a.m.
NED2 Entity disambiguation (via description) batch_6a016a46409881908ea7e93fd31cd5c5 completed May 11, 2026, 5:33 a.m.
Created at: April 10, 2026, 5:38 a.m.