Triple

T7219900
Position Surface form Disambiguated ID Type / Status
Subject Sir Visto E150229 entity
Predicate damsire P56417 FINISHED
Object Macaroni
Macaroni was a notable 19th-century British Thoroughbred racehorse and influential sire in bloodlines of classic winners.
 E649695 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: Macaroni | Statement: [Sir Visto, damsire, Macaroni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Macaroni
Context triple: [Sir Visto, damsire, Macaroni]
  • A. Penne
    Penne is a historic hill town in Italy’s Abruzzo region, notable for its ancient Vestini roots and well-preserved medieval architecture.
  • B. Spaghettii
    "Spaghettii" is a song by Beyoncé from her genre-blending album "Cowboy Carter," showcasing her experimental approach to country and hip-hop influences.
  • C. Noodles
    Noodles is the stage name and alias of Masta Killa, a member of the influential hip-hop group Wu-Tang Clan.
  • D. Noodles
    Noodles is the lead guitarist of the American punk rock band The Offspring, known for his energetic playing style and long tenure with the group.
  • E. Lasagne
    Lasagne is a lightweight Python library for building and training neural networks, designed to run on top of the Theano deep learning framework.
  • 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: Macaroni
Triple: [Sir Visto, damsire, Macaroni]
Generated description
Macaroni was a notable 19th-century British Thoroughbred racehorse and influential sire in bloodlines of classic winners.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Macaroni
Target entity description: Macaroni was a notable 19th-century British Thoroughbred racehorse and influential sire in bloodlines of classic winners.
  • A. Penne
    Penne is a historic hill town in Italy’s Abruzzo region, notable for its ancient Vestini roots and well-preserved medieval architecture.
  • B. Spaghettii
    "Spaghettii" is a song by Beyoncé from her genre-blending album "Cowboy Carter," showcasing her experimental approach to country and hip-hop influences.
  • C. Noodles
    Noodles is the stage name and alias of Masta Killa, a member of the influential hip-hop group Wu-Tang Clan.
  • D. Noodles
    Noodles is the lead guitarist of the American punk rock band The Offspring, known for his energetic playing style and long tenure with the group.
  • E. Lasagne
    Lasagne is a lightweight Python library for building and training neural networks, designed to run on top of the Theano deep learning framework.
  • 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_69c687effb44819092b95d07d0368c9f completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6e9b1a7908190bd215ffb84592e32 completed March 27, 2026, 8:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cc014fb88190818e12b7abe90c0a completed March 28, 2026, 12:39 p.m.
NEDg Description generation batch_69c7ccf3cd4c8190babc9e0e6b9f4371 completed March 28, 2026, 12:43 p.m.
NED2 Entity disambiguation (via description) batch_69c7cd5cedd88190b72df89b068c4483 completed March 28, 2026, 12:45 p.m.
Created at: March 27, 2026, 2:53 p.m.