Triple

T8776897
Position Surface form Disambiguated ID Type / Status
Subject Mr. Me Too E208606 entity
Predicate follows P134 FINISHED
Object Hot Damn
Hot Damn is a hip hop song by Clipse known for its gritty production and sharp, boastful lyricism.
 E756456 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 Damn | Statement: [Mr. Me Too, follows, Hot Damn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hot Damn
Context triple: [Mr. Me Too, follows, Hot Damn]
  • A. So Damn Happy
    So Damn Happy is a live album by American singer-songwriter Loudon Wainwright III, showcasing his witty, autobiographical folk songs and storytelling performances.
  • B. Too Darn Hot
    "Too Darn Hot" is a popular jazz-standard show tune by Cole Porter, originally written for the 1948 musical *Kiss Me, Kate* and later widely recorded by prominent vocalists.
  • C. Dammit
    "Dammit" is a fast-paced pop-punk song by Blink-182, widely recognized as one of their breakout hits from the late 1990s.
  • D. Lit Up
    "Lit Up" is a song by the American rock band Alligator.
  • E. Let 'Em In
    "Let 'Em In" is a 1976 soft rock song by Paul McCartney and Wings, known for its laid-back groove, prominent use of bells, and lyrics that name-check various friends and family members.
  • 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 Damn
Triple: [Mr. Me Too, follows, Hot Damn]
Generated description
Hot Damn is a hip hop song by Clipse known for its gritty production and sharp, boastful lyricism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hot Damn
Target entity description: Hot Damn is a hip hop song by Clipse known for its gritty production and sharp, boastful lyricism.
  • A. So Damn Happy
    So Damn Happy is a live album by American singer-songwriter Loudon Wainwright III, showcasing his witty, autobiographical folk songs and storytelling performances.
  • B. Too Darn Hot
    "Too Darn Hot" is a popular jazz-standard show tune by Cole Porter, originally written for the 1948 musical *Kiss Me, Kate* and later widely recorded by prominent vocalists.
  • C. Dammit
    "Dammit" is a fast-paced pop-punk song by Blink-182, widely recognized as one of their breakout hits from the late 1990s.
  • D. Lit Up
    "Lit Up" is a song by the American rock band Alligator.
  • E. Let 'Em In
    "Let 'Em In" is a 1976 soft rock song by Paul McCartney and Wings, known for its laid-back groove, prominent use of bells, and lyrics that name-check various friends and family members.
  • 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_69ca835fbee88190bf625939bac48d7f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f5086088190b317cf2aac7bee83 completed March 31, 2026, 11:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf51ceee2c81908d521cc4931e25dd completed April 3, 2026, 5:36 a.m.
NEDg Description generation batch_69cf53a27e2c8190a639d3b1007c11c3 completed April 3, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69cf54129d888190b61d67f99ad36cb8 completed April 3, 2026, 5:45 a.m.
Created at: March 30, 2026, 6:42 p.m.