Triple

T8120157
Position Surface form Disambiguated ID Type / Status
Subject Fiorello H. La Guardia E189584 entity
Predicate hasFamilyName P18 FINISHED
Object La Guardia E189584 NE FINISHED

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: La Guardia | Statement: [Fiorello H. La Guardia, hasFamilyName, La Guardia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Guardia
Context triple: [Fiorello H. La Guardia, hasFamilyName, La Guardia]
  • A. La Guardia chosen
    La Guardia is an Italian-origin surname most famously associated with Fiorello H. La Guardia, the influential three-term mayor of New York City in the early 20th century.
  • B. Guardea
    Guardea is a small Italian town and comune in the Umbria region, known for its medieval historic center and scenic position overlooking the Tiber Valley.
  • C. Inner Guard
    The Inner Guard is a Masonic lodge officer responsible for guarding the entrance from within and controlling admission to meetings.
  • D. The Guard
    The Guard is a darkly comedic Irish crime film in which Brendan Gleeson plays an unconventional small-town police officer drawn into an international drug-smuggling investigation.
  • E. Guards
    Guards is an honorific military designation historically awarded to elite, highly distinguished units in various armed forces, particularly in the Soviet and Russian militaries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82bb74848190afb1f18640632c10 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4359f3dc8190a2330cf6efb8c084 completed March 31, 2026, 3:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc944d009c81908ceb37b6922efb59 completed April 1, 2026, 3:43 a.m.
Created at: March 30, 2026, 5:33 p.m.