Triple

T6809198
Position Surface form Disambiguated ID Type / Status
Subject Alec Waugh E156586 entity
Predicate notableWork P4 FINISHED
Object Hot Countries
"Hot Countries" is a 1930 novel by British writer Alec Waugh, set in the tropics and exploring themes of colonial life, desire, and moral conflict.
 E619521 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: Hot Countries | Statement: [Alec Waugh, notableWork, Hot Countries]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hot Countries
Context triple: [Alec Waugh, notableWork, Hot Countries]
  • A. Hot
    "Hot" is a popular trap song by American rapper Young Thug, known for its brass-heavy production and memorable hook.
  • B. Hot Stuff
    "Hot Stuff" is a 1979 disco hit by Donna Summer that blends dance rhythms with rock influences and became one of her signature songs.
  • C. Heat
    Heat is a 1995 crime thriller film directed by Michael Mann, renowned for its intense heist sequences and the iconic pairing of Al Pacino and Robert De Niro.
  • D. Heat
    Heat is a chapter or section within the novel "Like Water for Chocolate" that focuses on themes of passion, desire, and emotional intensity.
  • E. Hot Topics
    Hot Topics is the opening discussion segment on the daytime talk show "The View," where the co-hosts debate and comment on current events and trending issues.
  • 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: Hot Countries
Triple: [Alec Waugh, notableWork, Hot Countries]
Generated description
"Hot Countries" is a 1930 novel by British writer Alec Waugh, set in the tropics and exploring themes of colonial life, desire, and moral conflict.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hot Countries
Target entity description: "Hot Countries" is a 1930 novel by British writer Alec Waugh, set in the tropics and exploring themes of colonial life, desire, and moral conflict.
  • A. Hot
    "Hot" is a popular trap song by American rapper Young Thug, known for its brass-heavy production and memorable hook.
  • B. Hot Stuff
    "Hot Stuff" is a 1979 disco hit by Donna Summer that blends dance rhythms with rock influences and became one of her signature songs.
  • C. Heat
    Heat is a 1995 crime thriller film directed by Michael Mann, renowned for its intense heist sequences and the iconic pairing of Al Pacino and Robert De Niro.
  • D. Heat
    Heat is a chapter or section within the novel "Like Water for Chocolate" that focuses on themes of passion, desire, and emotional intensity.
  • E. Hot Topics
    Hot Topics is the opening discussion segment on the daytime talk show "The View," where the co-hosts debate and comment on current events and trending issues.
  • 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_69c68828b26c819090fe9df7612bbc27 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d30c741881909e220b05aa564bc2 completed March 27, 2026, 6:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71aa5411c81908d05bef3213b39f1 completed March 28, 2026, 12:02 a.m.
NEDg Description generation batch_69c71b97125c81909f60a898d6bd4ebc completed March 28, 2026, 12:06 a.m.
NED2 Entity disambiguation (via description) batch_69c71c355b14819093909be7ee005e31 completed March 28, 2026, 12:09 a.m.
Created at: March 27, 2026, 2:16 p.m.