Triple

T4447072
Position Surface form Disambiguated ID Type / Status
Subject Raising Hell E96314 entity
Predicate hasPart P35 FINISHED
Object Peter Piper
Peter Piper is a classic English-language tongue-twister character best known from the rhyme about picking a peck of pickled peppers.
 E440963 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: Peter Piper | Statement: [Raising Hell, hasPart, Peter Piper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Peter Piper
Context triple: [Raising Hell, hasPart, Peter Piper]
  • A. Pete
    Pete is a common masculine given name, typically used as a familiar or informal form of the name Peter.
  • B. Pete
    Pete is a classic Disney cartoon villain, best known as Mickey Mouse’s burly, antagonistic foe in the Mickey Mouse franchise.
  • C. Pete
    Pete is a fictional character known as the son of Uncle Tom in Harriet Beecher Stowe’s anti-slavery novel "Uncle Tom’s Cabin."
  • D. Pete
    Pete is the nickname of Grover Cleveland Alexander, a Hall of Fame Major League Baseball pitcher and one of the greatest hurlers of the early 20th century.
  • E. Pete
    Pete is the young orphaned boy who befriends and is protected by a friendly dragon in the Disney film "Pete's Dragon."
  • 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: Peter Piper
Triple: [Raising Hell, hasPart, Peter Piper]
Generated description
Peter Piper is a classic English-language tongue-twister character best known from the rhyme about picking a peck of pickled peppers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Peter Piper
Target entity description: Peter Piper is a classic English-language tongue-twister character best known from the rhyme about picking a peck of pickled peppers.
  • A. Pete
    Pete is a common masculine given name, typically used as a familiar or informal form of the name Peter.
  • B. Pete
    Pete is a classic Disney cartoon villain, best known as Mickey Mouse’s burly, antagonistic foe in the Mickey Mouse franchise.
  • C. Pete
    Pete is a fictional character known as the son of Uncle Tom in Harriet Beecher Stowe’s anti-slavery novel "Uncle Tom’s Cabin."
  • D. Pete
    Pete is the nickname of Grover Cleveland Alexander, a Hall of Fame Major League Baseball pitcher and one of the greatest hurlers of the early 20th century.
  • E. Pete
    Pete is the young orphaned boy who befriends and is protected by a friendly dragon in the Disney film "Pete's Dragon."
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355d31e10819086590b9f828d50b0 completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b61386df48819080e44a23b9d67d23 completed March 15, 2026, 2:03 a.m.
NEDg Description generation batch_69b617c13d4481909d22d201ce405d3a completed March 15, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_69b6187687f8819084e2d611e9e31f79 completed March 15, 2026, 2:24 a.m.
Created at: March 12, 2026, 11:32 p.m.