Triple

T6269579
Position Surface form Disambiguated ID Type / Status
Subject Mr. Telephone Man E140494 entity
Predicate followedBySingle P134 FINISHED
Object Lost in Love
"Lost in Love" is a song best known as a soft rock ballad popularized by the Australian duo Air Supply.
E579733 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: Lost in Love | Statement: [Mr. Telephone Man, followedBySingle, Lost in Love]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lost in Love
Context triple: [Mr. Telephone Man, followedBySingle, Lost in Love]
  • A. Lost in Love
    "Lost in Love" is a song by the American R&B group New Edition, showcasing their signature harmonies and romantic ballad style.
  • B. Still in Love
    "Still in Love" is an R&B song by American singer-songwriter Brian McKnight, showcasing his smooth vocals and romantic ballad style.
  • C. Love Is Gone
    "Love Is Gone" is a popular electronic dance track by French DJ and producer David Guetta that helped cement his rise in the international EDM scene.
  • D. Stuck in Love
    Stuck in Love is a 2012 romantic comedy-drama film that follows a dysfunctional family of writers as they navigate love, heartbreak, and reconciliation over the course of a year.
  • E. Without Love
    "Without Love" is a lively duet-turned-ensemble love song from the musical Hairspray, celebrating young romance and defiance of social barriers.
  • 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: Lost in Love
Triple: [Mr. Telephone Man, followedBySingle, Lost in Love]
Generated description
"Lost in Love" is a song best known as a soft rock ballad popularized by the Australian duo Air Supply.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lost in Love
Target entity description: "Lost in Love" is a song best known as a soft rock ballad popularized by the Australian duo Air Supply.
  • A. Lost in Love
    "Lost in Love" is a song by the American R&B group New Edition, showcasing their signature harmonies and romantic ballad style.
  • B. Still in Love
    "Still in Love" is an R&B song by American singer-songwriter Brian McKnight, showcasing his smooth vocals and romantic ballad style.
  • C. Love Is Gone
    "Love Is Gone" is a popular electronic dance track by French DJ and producer David Guetta that helped cement his rise in the international EDM scene.
  • D. Stuck in Love
    Stuck in Love is a 2012 romantic comedy-drama film that follows a dysfunctional family of writers as they navigate love, heartbreak, and reconciliation over the course of a year.
  • E. Without Love
    "Without Love" is a lively duet-turned-ensemble love song from the musical Hairspray, celebrating young romance and defiance of social barriers.
  • 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_69c008cabc4081909723e2547c9d6cc0 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063a3f1d081908ccff88db94b1f9c completed March 22, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c24460f1bc8190b15ca58331410ec2 completed March 24, 2026, 7:59 a.m.
NEDg Description generation batch_69c2a5a6157c8190a57a297cf606eecb completed March 24, 2026, 2:54 p.m.
NED2 Entity disambiguation (via description) batch_69c2a60a92cc8190847e242482788ff3 completed March 24, 2026, 2:56 p.m.
Created at: March 22, 2026, 4:25 p.m.