Triple

T19779838
Position Surface form Disambiguated ID Type / Status
Subject Guido Cantelli E475101 entity
Predicate givenName P17 FINISHED
Object Guido NE NERFINISHED

How this triple was built (2 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: Guido | Statement: [Guido Cantelli, givenName, Guido]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guido
Context triple: [Guido Cantelli, givenName, Guido]
  • A. Guido chosen
    Guido is a masculine given name of Italian origin, famously borne by Guido van Rossum, the creator of the Python programming language.
  • B. Guido
    Guido is a small, enthusiastic Italian forklift from Pixar's Cars franchise who works as Luigi's tire-changing assistant in Radiator Springs.
  • C. Guido
    Guido is a character associated with Joel Goodson in the 1983 film "Risky Business," often linked to the movie’s themes of youthful risk and moral ambiguity.
  • D. Count Guido Franceschini
    Count Guido Franceschini is the aristocratic Italian husband and murderer at the center of Robert Browning’s verse novel "The Ring and the Book," whose trial and crime drive the poem’s dramatic exploration of truth and morality.
  • E. Guido Bruno
    Guido Bruno was an early 20th-century Greenwich Village bohemian, editor, and publisher known for promoting avant-garde and controversial literature.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51a43a08190956bc6df13c91a77 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65382ff308190832800dd60675f7a completed April 20, 2026, 4:25 p.m.
Created at: April 10, 2026, 1:49 p.m.