Triple

T2010342
Position Surface form Disambiguated ID Type / Status
Subject Ladies of the Canyon E43674 entity
Predicate hasTrack P3284 FINISHED
Object For Free
"For Free" is a reflective folk song by Joni Mitchell that contrasts commercial success with the purity of a street musician’s art.
E225682 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: For Free | Statement: [Ladies of the Canyon, hasTrack, For Free]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: For Free
Context triple: [Ladies of the Canyon, hasTrack, For Free]
  • A. Libre
    Libre is a popular Yves Saint Laurent fragrance known for its bold, modern floral scent that blends lavender, orange blossom, and vanilla.
  • B. Feel Free
    Feel Free is a 2018 essay collection by British author Zadie Smith that explores culture, politics, literature, and personal experience with her characteristic wit and insight.
  • C. Be Free
    "Be Free" is a song by the Black Eyed Peas featured on their debut studio album "Behind the Front."
  • D. Carefree
    "Carefree" is a 1938 musical comedy film starring Fred Astaire and Ginger Rogers, known for its blend of dance, romance, and screwball humor.
  • E. Free to Love
    "Free to Love" is a novel by Ivana Trump that blends romance and high society drama, drawing on her experiences in the worlds of wealth, fashion, and power.
  • 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: For Free
Triple: [Ladies of the Canyon, hasTrack, For Free]
Generated description
"For Free" is a reflective folk song by Joni Mitchell that contrasts commercial success with the purity of a street musician’s art.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: For Free
Target entity description: "For Free" is a reflective folk song by Joni Mitchell that contrasts commercial success with the purity of a street musician’s art.
  • A. Libre
    Libre is a popular Yves Saint Laurent fragrance known for its bold, modern floral scent that blends lavender, orange blossom, and vanilla.
  • B. Feel Free
    Feel Free is a 2018 essay collection by British author Zadie Smith that explores culture, politics, literature, and personal experience with her characteristic wit and insight.
  • C. Be Free
    "Be Free" is a song by the Black Eyed Peas featured on their debut studio album "Behind the Front."
  • D. Carefree
    "Carefree" is a 1938 musical comedy film starring Fred Astaire and Ginger Rogers, known for its blend of dance, romance, and screwball humor.
  • E. Free to Love
    "Free to Love" is a novel by Ivana Trump that blends romance and high society drama, drawing on her experiences in the worlds of wealth, fashion, and power.
  • 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_69a88716e9f08190946313fdc949e3cf completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8afe6f8819092679c86d1f2d041 completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0ae5f0748190aecee47884c61ecc completed March 8, 2026, 11:48 p.m.
NEDg Description generation batch_69ae0bab9d7c8190acde67a6301e18ec completed March 8, 2026, 11:52 p.m.
NED2 Entity disambiguation (via description) batch_69ae0c2fe1a88190867b1d533d58b7fc completed March 8, 2026, 11:54 p.m.
Created at: March 4, 2026, 7:37 p.m.