Triple

T7182296
Position Surface form Disambiguated ID Type / Status
Subject Ed Macauley E167477 entity
Predicate nickname P55 FINISHED
Object Easy Ed
Easy Ed was the nickname of Ed Macauley, a Hall of Fame American professional basketball player known for his scoring and versatility in the early NBA.
 E647713 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 Ed | Statement: [Ed Macauley, nickname, Easy Ed]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Easy Ed
Context triple: [Ed Macauley, nickname, Easy Ed]
  • A. Easy
    "Easy" is a track from Kanye West's album *Donda 2*, notable for its raw, confrontational lyrics and high-profile collaborations.
  • B. Easy
    Easy is a South American home improvement and construction retail chain known for selling building materials, tools, and household products.
  • C. Easy
    "Easy" is a song by Joanna Newsom from her 2010 triple album *Have One on Me*, noted for its intricate harp arrangements and poetic lyrics.
  • D. Easy
    "Easy" is a soulful 1977 ballad by the Commodores, written and sung by Lionel Richie, that became one of the group's signature hits.
  • E. Easy
    Easy is an anthology-style Netflix comedy-drama series created by Joe Swanberg that explores modern relationships, sex, and technology in Chicago through loosely connected stories.
  • 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 Ed
Triple: [Ed Macauley, nickname, Easy Ed]
Generated description
Easy Ed was the nickname of Ed Macauley, a Hall of Fame American professional basketball player known for his scoring and versatility in the early NBA.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Easy Ed
Target entity description: Easy Ed was the nickname of Ed Macauley, a Hall of Fame American professional basketball player known for his scoring and versatility in the early NBA.
  • A. Easy
    "Easy" is a track from Kanye West's album *Donda 2*, notable for its raw, confrontational lyrics and high-profile collaborations.
  • B. Easy
    Easy is a South American home improvement and construction retail chain known for selling building materials, tools, and household products.
  • C. Easy
    "Easy" is a song by Joanna Newsom from her 2010 triple album *Have One on Me*, noted for its intricate harp arrangements and poetic lyrics.
  • D. Easy
    "Easy" is a soulful 1977 ballad by the Commodores, written and sung by Lionel Richie, that became one of the group's signature hits.
  • E. Easy
    Easy is an anthology-style Netflix comedy-drama series created by Joe Swanberg that explores modern relationships, sex, and technology in Chicago through loosely connected stories.
  • 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_69c6888a7c548190a3d39b52a393080f completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e8bc25088190a7d7f3ba2461b5e9 completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b94390d48190b7443c9c8cc41625 completed March 28, 2026, 11:19 a.m.
NEDg Description generation batch_69c7b9c1afe48190bc55468790e84067 completed March 28, 2026, 11:21 a.m.
NED2 Entity disambiguation (via description) batch_69c7ba441f8c8190a4f88b140a1563f9 completed March 28, 2026, 11:23 a.m.
Created at: March 27, 2026, 2:49 p.m.