Triple

T6995575
Position Surface form Disambiguated ID Type / Status
Subject Kiersey Clemons E162203 entity
Predicate notableWork P4 FINISHED
Object Easy (TV series)
Easy is an American anthology comedy-drama television series created by Joe Swanberg that explores modern love, relationships, and technology through loosely connected stories set in Chicago.
 E634441 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: Easy (TV series) | Statement: [Kiersey Clemons, notableWork, Easy (TV series)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Easy (TV series)
Context triple: [Kiersey Clemons, notableWork, Easy (TV series)]
  • A. Nice ’n’ Easy
    Nice ’n’ Easy is a popular song with lyrics by Alan and Marilyn Bergman, best known through Frank Sinatra’s smooth, laid-back 1960 recording.
  • B. EZY
    EZY is the ICAO airline designator used for flights operated by the British low-cost carrier easyJet.
  • C. So Simple
    "So Simple" is a song by American singer-songwriter Alicia Keys from her album "The Diary of Alicia Keys."
  • D. Too Easy
    "Too Easy" is a song by Kanye West featured on his album "Donda 2."
  • E. Easy A
    Easy A is a 2010 teen comedy film that satirizes high school culture and social reputation, starring Emma Stone as a student whose fabricated promiscuity spirals out of control.
  • 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: Easy (TV series)
Triple: [Kiersey Clemons, notableWork, Easy (TV series)]
Generated description
Easy is an American anthology comedy-drama television series created by Joe Swanberg that explores modern love, relationships, and technology through loosely connected stories set in Chicago.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Easy (TV series)
Target entity description: Easy is an American anthology comedy-drama television series created by Joe Swanberg that explores modern love, relationships, and technology through loosely connected stories set in Chicago.
  • A. Nice ’n’ Easy
    Nice ’n’ Easy is a popular song with lyrics by Alan and Marilyn Bergman, best known through Frank Sinatra’s smooth, laid-back 1960 recording.
  • B. EZY
    EZY is the ICAO airline designator used for flights operated by the British low-cost carrier easyJet.
  • C. So Simple
    "So Simple" is a song by American singer-songwriter Alicia Keys from her album "The Diary of Alicia Keys."
  • D. Too Easy
    "Too Easy" is a song by Kanye West featured on his album "Donda 2."
  • E. Easy A
    Easy A is a 2010 teen comedy film that satirizes high school culture and social reputation, starring Emma Stone as a student whose fabricated promiscuity spirals out of control.
  • 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_69c68857ffc08190857dc62cd5253777 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbec259c8190bb4cfbc1ff6fc786 completed March 27, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a1fa11481908450978acc1e0913 completed March 28, 2026, 5:41 a.m.
NEDg Description generation batch_69c76b84f5688190a0aef7cd8695c6b0 completed March 28, 2026, 5:47 a.m.
NED2 Entity disambiguation (via description) batch_69c76be95ecc8190a57ff197f236d434 completed March 28, 2026, 5:49 a.m.
Created at: March 27, 2026, 2:32 p.m.