Triple

T6239913
Position Surface form Disambiguated ID Type / Status
Subject Some Lessons Learned E139572 entity
Predicate hasTrack P3284 FINISHED
Object If You Hadn't Been There
"If You Hadn't Been There" is a song featured on the album *Some Lessons Learned* by Kristin Chenoweth.
 E578838 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: If You Hadn't Been There | Statement: [Some Lessons Learned, hasTrack, If You Hadn't Been There]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: If You Hadn't Been There
Context triple: [Some Lessons Learned, hasTrack, If You Hadn't Been There]
  • A. I Was There
    "I Was There" is a song by the American punk rock band Green Day, featured on their debut studio album 39/Smooth.
  • B. I Was There
    "I Was There" is the memoir of Fleet Admiral William D. Leahy, offering an insider’s account of high-level Allied strategy and decision-making during World War II.
  • C. You Could Have Been with Me
    "You Could Have Been with Me" is a 1981 pop album by Scottish singer Sheena Easton that helped solidify her early international success.
  • D. If There Was Love
    "If There Was Love" is a song featured on the album "Results" by Liza Minnelli.
  • E. Anywhere but Here
    Anywhere but Here is a 1986 coming-of-age novel by Mona Simpson that follows a restless mother and her precocious daughter as they leave the Midwest for California in search of a better life.
  • 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: If You Hadn't Been There
Triple: [Some Lessons Learned, hasTrack, If You Hadn't Been There]
Generated description
"If You Hadn't Been There" is a song featured on the album *Some Lessons Learned* by Kristin Chenoweth.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: If You Hadn't Been There
Target entity description: "If You Hadn't Been There" is a song featured on the album *Some Lessons Learned* by Kristin Chenoweth.
  • A. I Was There
    "I Was There" is a song by the American punk rock band Green Day, featured on their debut studio album 39/Smooth.
  • B. I Was There
    "I Was There" is the memoir of Fleet Admiral William D. Leahy, offering an insider’s account of high-level Allied strategy and decision-making during World War II.
  • C. You Could Have Been with Me
    "You Could Have Been with Me" is a 1981 pop album by Scottish singer Sheena Easton that helped solidify her early international success.
  • D. If There Was Love
    "If There Was Love" is a song featured on the album "Results" by Liza Minnelli.
  • E. Anywhere but Here
    Anywhere but Here is a 1986 coming-of-age novel by Mona Simpson that follows a restless mother and her precocious daughter as they leave the Midwest for California in search of a better life.
  • 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_69c008b0e7ac8190808a59573ee646f3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063067d9c819085a18d9d03939266 completed March 22, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20e07bff8819091ca881c9b4daaf6 completed March 24, 2026, 4:07 a.m.
NEDg Description generation batch_69c214aaef308190be1166c1389bf3d3 completed March 24, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_69c21508dbec8190b9bb4806a83ecb13 completed March 24, 2026, 4:37 a.m.
Created at: March 22, 2026, 4:23 p.m.