Triple

T11345294
Position Surface form Disambiguated ID Type / Status
Subject Alabama 3 E268696 entity
Predicate notableSong P4 FINISHED
Object Too Sick to Pray
"Too Sick to Pray" is a song by the British band Alabama 3, known for their fusion of country, blues, and electronic music.
 E919998 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: Too Sick to Pray | Statement: [Alabama 3, notableSong, Too Sick to Pray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Too Sick to Pray
Context triple: [Alabama 3, notableSong, Too Sick to Pray]
  • A. Too Sick to Pray
    "Too Sick to Pray" is a song by the American rock band Spirit, known for blending psychedelic rock with jazz and folk influences.
  • B. So Sick
    "So Sick" is a popular R&B song by Ne-Yo, known for its melancholic theme of heartbreak and its success as one of his breakthrough hits.
  • C. Sick of Me
    "Sick of Me" is a song by the American rock band Shinedown from their album "Shenanigans."
  • D. Sick of It
    Sick of It is a British comedy-drama television series starring Karl Pilkington as both a disillusioned cab driver and the voice of his inner self.
  • E. Love Sick
    "Love Sick" is a song by Bob Dylan, best known as the haunting, blues-infused opening track of his 1997 album *Time Out of Mind*.
  • 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: Too Sick to Pray
Triple: [Alabama 3, notableSong, Too Sick to Pray]
Generated description
"Too Sick to Pray" is a song by the British band Alabama 3, known for their fusion of country, blues, and electronic music.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Too Sick to Pray
Target entity description: "Too Sick to Pray" is a song by the British band Alabama 3, known for their fusion of country, blues, and electronic music.
  • A. Too Sick to Pray
    "Too Sick to Pray" is a song by the American rock band Spirit, known for blending psychedelic rock with jazz and folk influences.
  • B. So Sick
    "So Sick" is a popular R&B song by Ne-Yo, known for its melancholic theme of heartbreak and its success as one of his breakthrough hits.
  • C. Sick of Me
    "Sick of Me" is a song by the American rock band Shinedown from their album "Shenanigans."
  • D. Sick of It
    Sick of It is a British comedy-drama television series starring Karl Pilkington as both a disillusioned cab driver and the voice of his inner self.
  • E. Love Sick
    "Love Sick" is a song by Bob Dylan, best known as the haunting, blues-infused opening track of his 1997 album *Time Out of Mind*.
  • 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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea1f9574819089760c5b5908f09e completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5436e9d848190a7e585351d24df03 completed April 19, 2026, 9:04 p.m.
NEDg Description generation batch_69e5474b77948190b2c45831871383e8 completed April 19, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_69e54eeba4a88190af128a99c277853a completed April 19, 2026, 9:53 p.m.
Created at: April 8, 2026, 9:33 p.m.