Triple

T1072802
Position Surface form Disambiguated ID Type / Status
Subject Macchi C.205 Veltro E23366 entity
Predicate nicknameMeaning P7596 FINISHED
Object Greyhound
Greyhound is a breed of tall, slender sighthound renowned for its exceptional speed and grace, historically used for hunting and racing.
 E126778 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: Greyhound | Statement: [Macchi C.205 Veltro, nicknameMeaning, Greyhound]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Greyhound
Context triple: [Macchi C.205 Veltro, nicknameMeaning, Greyhound]
  • A. Greyhound
    Greyhound is a 2020 World War II naval thriller film starring Tom Hanks as a U.S. destroyer captain escorting Allied convoys across the Atlantic while evading German U-boats.
  • B. Bulldogs
    Bulldogs is the nickname of Yale University's men's basketball team, a historic Ivy League program competing in NCAA Division I.
  • C. Bulldogs
    Bulldogs is the mascot and collective nickname commonly associated with various sports teams, notably those of California State University, Fresno.
  • D. Bulldogs
    Bulldogs is the nickname for the athletic teams representing Yale University in collegiate sports.
  • E. Landseer
    Landseer is the middle name of renowned British architect Sir Edwin Lutyens, best known for his influential country houses and war memorial designs.
  • 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: Greyhound
Triple: [Macchi C.205 Veltro, nicknameMeaning, Greyhound]
Generated description
Greyhound is a breed of tall, slender sighthound renowned for its exceptional speed and grace, historically used for hunting and racing.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Greyhound
Target entity description: Greyhound is a breed of tall, slender sighthound renowned for its exceptional speed and grace, historically used for hunting and racing.
  • A. Greyhound
    Greyhound is a 2020 World War II naval thriller film starring Tom Hanks as a U.S. destroyer captain escorting Allied convoys across the Atlantic while evading German U-boats.
  • B. Bulldogs
    Bulldogs is the nickname of Yale University's men's basketball team, a historic Ivy League program competing in NCAA Division I.
  • C. Bulldogs
    Bulldogs is the mascot and collective nickname commonly associated with various sports teams, notably those of California State University, Fresno.
  • D. Bulldogs
    Bulldogs is the nickname for the athletic teams representing Yale University in collegiate sports.
  • E. Landseer
    Landseer is the middle name of renowned British architect Sir Edwin Lutyens, best known for his influential country houses and war memorial designs.
  • 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_69a493ee1f908190992b5f0d1b04459b completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b92afad88190b7705923f71fc760 completed March 1, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c1fb7948190b08c95e68d3de00e completed March 7, 2026, 4:02 p.m.
NEDg Description generation batch_69ac4e9e68688190a02550b270660a50 completed March 7, 2026, 4:13 p.m.
NED2 Entity disambiguation (via description) batch_69ac4f2475048190a5e58bf8320e91d4 completed March 7, 2026, 4:15 p.m.
Created at: March 1, 2026, 7:42 p.m.