Triple

T5193744
Position Surface form Disambiguated ID Type / Status
Subject Meghan Trainor E117216 entity
Predicate notableAlbum P4 FINISHED
Object Thank You
"Thank You" is Meghan Trainor's second major-label studio album, showcasing a more mature pop and R&B-influenced sound and featuring hits like "No" and "Me Too."
 E501258 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: Thank You | Statement: [Meghan Trainor, notableAlbum, Thank You]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Thank You
Context triple: [Meghan Trainor, notableAlbum, Thank You]
  • A. Thank You
    "Thank You" is a 1995 studio album by the American rock band Royal Trux, known for its experimental, lo-fi blend of noise rock and classic rock influences.
  • B. Thank You
    "Thank You" is a song featured on the jazz standard album "All of Me."
  • C. Thank You
    "Thank You" is a soulful R&B song by British singer-songwriter Estelle, showcasing her smooth vocals and heartfelt lyricism.
  • D. Thank You So Much
    "Thank You So Much" is a lesser-known song composed by Richard Rodgers, the influential American composer famed for his work in musical theatre.
  • E. Thank You for the Music
    "Thank You for the Music" is a popular ABBA song, later featured prominently in the musical and film "Mamma Mia!" where it is performed by the character Harry Bright among others.
  • 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: Thank You
Triple: [Meghan Trainor, notableAlbum, Thank You]
Generated description
"Thank You" is Meghan Trainor's second major-label studio album, showcasing a more mature pop and R&B-influenced sound and featuring hits like "No" and "Me Too."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Thank You
Target entity description: "Thank You" is Meghan Trainor's second major-label studio album, showcasing a more mature pop and R&B-influenced sound and featuring hits like "No" and "Me Too."
  • A. Thank You
    "Thank You" is a song featured on the jazz standard album "All of Me."
  • B. Thank You
    "Thank You" is a 1995 studio album by the American rock band Royal Trux, known for its experimental, lo-fi blend of noise rock and classic rock influences.
  • C. Thank You
    "Thank You" is a soulful R&B song by British singer-songwriter Estelle, showcasing her smooth vocals and heartfelt lyricism.
  • D. Thank You So Much
    "Thank You So Much" is a lesser-known song composed by Richard Rodgers, the influential American composer famed for his work in musical theatre.
  • E. Thank You for the Music
    "Thank You for the Music" is a popular ABBA song, later featured prominently in the musical and film "Mamma Mia!" where it is performed by the character Harry Bright among others.
  • 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_69bd4462ed04819084fcb01eb9d2fa74 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79f142488190bc6c57b8ff7ef894 completed March 20, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69bee09743e08190a3a73fb410a6f124 completed March 21, 2026, 6:16 p.m.
NEDg Description generation batch_69bee5a7cc748190b5df14b78aeac608 completed March 21, 2026, 6:38 p.m.
NED2 Entity disambiguation (via description) batch_69bee64966f88190874edda00332e220 completed March 21, 2026, 6:41 p.m.
Created at: March 20, 2026, 1:46 p.m.