Triple

T15938074
Position Surface form Disambiguated ID Type / Status
Subject Caught in the Game E386488 entity
Predicate hasPart P35 FINISHED
Object Slander
"Slander" is a song by the American rock band Survivor, featured on their 1983 album *Caught in the Game*.
 E1184498 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: Slander | Statement: [Caught in the Game, hasPart, Slander]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Slander
Context triple: [Caught in the Game, hasPart, Slander]
  • A. Libel
    Libel is a 1929 Broadway courtroom drama play by Maurine Dallas Watkins that explores themes of defamation, reputation, and truth.
  • B. The Slanderer
    The Slanderer is an English rendering of the title of Surah Al-Humazah, a chapter of the Qur’an that condemns backbiting, slander, and the hoarding of wealth.
  • C. Swear
    "Swear" is a pop song by Sheena Easton from her 1984 album *A Private Heaven*, reflecting the synth-driven, romantic style of mid-1980s adult contemporary music.
  • D. Publikumsbeschimpfung
    Publikumsbeschimpfung is an experimental 1966 play by Austrian writer Peter Handke that provocatively breaks theatrical conventions by directly attacking and confronting the audience.
  • E. Sarca
    The Sarca is a river in northern Italy that flows through the Trentino region and ultimately feeds into Lake Garda.
  • 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: Slander
Triple: [Caught in the Game, hasPart, Slander]
Generated description
"Slander" is a song by the American rock band Survivor, featured on their 1983 album *Caught in the Game*.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Slander
Target entity description: "Slander" is a song by the American rock band Survivor, featured on their 1983 album *Caught in the Game*.
  • A. Libel
    Libel is a 1929 Broadway courtroom drama play by Maurine Dallas Watkins that explores themes of defamation, reputation, and truth.
  • B. The Slanderer
    The Slanderer is an English rendering of the title of Surah Al-Humazah, a chapter of the Qur’an that condemns backbiting, slander, and the hoarding of wealth.
  • C. Swear
    "Swear" is a pop song by Sheena Easton from her 1984 album *A Private Heaven*, reflecting the synth-driven, romantic style of mid-1980s adult contemporary music.
  • D. Publikumsbeschimpfung
    Publikumsbeschimpfung is an experimental 1966 play by Austrian writer Peter Handke that provocatively breaks theatrical conventions by directly attacking and confronting the audience.
  • E. Sarca
    The Sarca is a river in northern Italy that flows through the Trentino region and ultimately feeds into Lake Garda.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156ac934c8190b6178eb66023252e completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5b8121881909b15bf6451d3d3a8 completed May 9, 2026, 10:31 p.m.
NEDg Description generation batch_69ffb718d60481908ac0034ed8d8abc5 completed May 9, 2026, 10:37 p.m.
NED2 Entity disambiguation (via description) batch_69ffb7c98cf8819097c7012040dbfe89 completed May 9, 2026, 10:40 p.m.
Created at: April 10, 2026, 4:53 a.m.