Triple

T2007317
Position Surface form Disambiguated ID Type / Status
Subject Carabinieri E43614 entity
Predicate hasRank P337 FINISHED
Object Appuntato
Appuntato is a non-commissioned officer rank within the Italian Carabinieri, roughly equivalent to a senior corporal.
E224373 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: Appuntato | Statement: [Carabinieri, hasRank, Appuntato]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Appuntato
Context triple: [Carabinieri, hasRank, Appuntato]
  • A. Mr. Papers
    Mr. Papers is a rapper best known for his on-and-off romantic relationship with hip-hop icon Lil' Kim.
  • B. Scoop
    Scoop is a satirical novel by Evelyn Waugh that lampoons sensationalist journalism and foreign correspondence.
  • C. La Dotta
    La Dotta is a nickname for the Italian city of Bologna, highlighting its historic role as a major center of learning and home to one of the world’s oldest universities.
  • D. De oratore
    De oratore is a philosophical dialogue by the Roman statesman Cicero that explores the theory and practice of rhetoric and ideal oratory.
  • E. The Autograph Man
    The Autograph Man is a novel by Zadie Smith that satirically explores celebrity culture, identity, and obsession through the life of a professional autograph collector in contemporary London.
  • 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: Appuntato
Triple: [Carabinieri, hasRank, Appuntato]
Generated description
Appuntato is a non-commissioned officer rank within the Italian Carabinieri, roughly equivalent to a senior corporal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Appuntato
Target entity description: Appuntato is a non-commissioned officer rank within the Italian Carabinieri, roughly equivalent to a senior corporal.
  • A. Mr. Papers
    Mr. Papers is a rapper best known for his on-and-off romantic relationship with hip-hop icon Lil' Kim.
  • B. Scoop
    Scoop is a satirical novel by Evelyn Waugh that lampoons sensationalist journalism and foreign correspondence.
  • C. La Dotta
    La Dotta is a nickname for the Italian city of Bologna, highlighting its historic role as a major center of learning and home to one of the world’s oldest universities.
  • D. De oratore
    De oratore is a philosophical dialogue by the Roman statesman Cicero that explores the theory and practice of rhetoric and ideal oratory.
  • E. The Autograph Man
    The Autograph Man is a novel by Zadie Smith that satirically explores celebrity culture, identity, and obsession through the life of a professional autograph collector in contemporary London.
  • 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_69a88716e9f08190946313fdc949e3cf completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8999e108190a07daa01452a5dab completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0ae12d708190bcfe91e3ab53f04e completed March 8, 2026, 11:48 p.m.
NEDg Description generation batch_69ae0b63b85c819096fc8ad12ace4d22 completed March 8, 2026, 11:50 p.m.
NED2 Entity disambiguation (via description) batch_69ae0bc55fcc8190bf117ef1328b8a76 completed March 8, 2026, 11:52 p.m.
Created at: March 4, 2026, 7:37 p.m.