Triple

T8860855
Position Surface form Disambiguated ID Type / Status
Subject Al Martino E210882 entity
Predicate notableWork P4 FINISHED
Object Mary in the Morning
"Mary in the Morning" is a romantic pop song popularized by American singer Al Martino in the 1960s.
 E762175 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: Mary in the Morning | Statement: [Al Martino, notableWork, Mary in the Morning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mary in the Morning
Context triple: [Al Martino, notableWork, Mary in the Morning]
  • A. Joy in the Morning
    "Joy in the Morning" is a comic novel in P. G. Wodehouse’s Jeeves and Wooster series, featuring Bertie Wooster’s misadventures and the ingenious problem-solving of his valet Jeeves.
  • B. Mary’s Song
    "Mary’s Song" is a contemplative poem by Sylvia Plath that juxtaposes the serenity of a winter landscape with themes of sacrifice and suffering.
  • C. Misty Morning
    Misty Morning is a song by Jamaican reggae artist Kaya, known for its mellow, atmospheric sound and reflective mood.
  • D. The Morning
    "The Morning" is a moody, atmospheric R&B track by The Weeknd, known for its hazy production and themes of hedonism and disillusionment.
  • E. The Morning
    "The Morning" is a painting by 18th-century French artist Joseph Vernet, best known for his atmospheric seascapes and landscape scenes.
  • 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: Mary in the Morning
Triple: [Al Martino, notableWork, Mary in the Morning]
Generated description
"Mary in the Morning" is a romantic pop song popularized by American singer Al Martino in the 1960s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mary in the Morning
Target entity description: "Mary in the Morning" is a romantic pop song popularized by American singer Al Martino in the 1960s.
  • A. Joy in the Morning
    "Joy in the Morning" is a comic novel in P. G. Wodehouse’s Jeeves and Wooster series, featuring Bertie Wooster’s misadventures and the ingenious problem-solving of his valet Jeeves.
  • B. Mary’s Song
    "Mary’s Song" is a contemplative poem by Sylvia Plath that juxtaposes the serenity of a winter landscape with themes of sacrifice and suffering.
  • C. Misty Morning
    Misty Morning is a song by Jamaican reggae artist Kaya, known for its mellow, atmospheric sound and reflective mood.
  • D. The Morning
    "The Morning" is a moody, atmospheric R&B track by The Weeknd, known for its hazy production and themes of hedonism and disillusionment.
  • E. The Morning
    "The Morning" is a painting by 18th-century French artist Joseph Vernet, best known for his atmospheric seascapes and landscape scenes.
  • 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_69ca838bbddc8190ab546d737e5d350f completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60e860888190a8a8702377db949e completed April 1, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0b94f5481909902b5fa405a502f completed April 3, 2026, 11:12 a.m.
NEDg Description generation batch_69cfa1714b4081909035c9b15c82c1be completed April 3, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_69cfa24be80481909e2b575f99cd1dc4 completed April 3, 2026, 11:19 a.m.
Created at: March 30, 2026, 6:50 p.m.