Triple

T299270
Position Surface form Disambiguated ID Type / Status
Subject chicken E6161 entity
Predicate hasCommonBreed P7254 FINISHED
Object Wyandotte
Wyandotte is a popular American dual-purpose chicken breed valued for its good egg production, meat quality, and attractive laced plumage.
E38912 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: Wyandotte | Statement: [chicken, hasCommonBreed, Wyandotte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wyandotte
Context triple: [chicken, hasCommonBreed, Wyandotte]
  • A. Goodhue
    Goodhue is a surname most notably associated with Bertram Grosvenor Goodhue, an influential American architect known for his Gothic Revival and early modernist designs.
  • B. Bessemer
    Bessemer is a surname most notably associated with Sir Henry Bessemer, the English inventor who revolutionized steel production in the 19th century.
  • C. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • D. Pendleton
    Pendleton is an inner-city district of Salford in Greater Manchester, England, known for its mix of residential areas, retail developments, and post-war social housing.
  • E. Marquette
    Marquette is a city in Michigan’s Upper Peninsula known as a key shipping and commercial hub on the southern shore of Lake Superior.
  • 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: Wyandotte
Triple: [chicken, hasCommonBreed, Wyandotte]
Generated description
Wyandotte is a popular American dual-purpose chicken breed valued for its good egg production, meat quality, and attractive laced plumage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wyandotte
Target entity description: Wyandotte is a popular American dual-purpose chicken breed valued for its good egg production, meat quality, and attractive laced plumage.
  • A. Goodhue
    Goodhue is a surname most notably associated with Bertram Grosvenor Goodhue, an influential American architect known for his Gothic Revival and early modernist designs.
  • B. Bessemer
    Bessemer is a surname most notably associated with Sir Henry Bessemer, the English inventor who revolutionized steel production in the 19th century.
  • C. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • D. Pendleton
    Pendleton is an inner-city district of Salford in Greater Manchester, England, known for its mix of residential areas, retail developments, and post-war social housing.
  • E. Marquette
    Marquette is a city in Michigan’s Upper Peninsula known as a key shipping and commercial hub on the southern shore of Lake Superior.
  • 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_69a2e79114b081909490b3bf5a5dbb51 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2ee002dd0819080f0841eb9107ee3 completed Feb. 28, 2026, 1:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3aba14b0881908eb4f62ac9261d63 completed March 1, 2026, 2:59 a.m.
NEDg Description generation batch_69a3af5161448190b2051c9533379b3e completed March 1, 2026, 3:15 a.m.
NED2 Entity disambiguation (via description) batch_69a3afb5fca48190a2bfece390311dca completed March 1, 2026, 3:17 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.