Triple

T10408673
Position Surface form Disambiguated ID Type / Status
Subject Leona E245330 entity
Predicate hasRelatedName P3889 FINISHED
Object Leonard E53541 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: Leonard | Statement: [Leona, hasRelatedName, Leonard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leonard
Context triple: [Leona, hasRelatedName, Leonard]
  • A. Leonard chosen
    Leonard is a masculine given name of Germanic origin, commonly used in English-speaking countries and borne by numerous notable figures in arts, sports, and public life.
  • B. Leonard Skinner
    Leonard Skinner was a high school gym teacher whose strict enforcement of hair-length rules famously inspired the name of the Southern rock band Lynyrd Skynyrd.
  • C. Laurence
    Laurence is a masculine given name of Latin origin, commonly used in English-speaking countries.
  • D. Léonard
    Léonard is a given name and surname used in French-speaking contexts, corresponding to the name Leonhard or Leonard.
  • E. Lenny Leonard
    Lenny Leonard is a recurring character on the animated TV show "The Simpsons," known as Homer Simpson’s affable, somewhat dim-witted coworker and close friend.
  • 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_69d381be340c8190b05998703d42d224 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9faa97c819092cadedadabe26bf completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fbf1c428819099ca359309c4c836 completed April 9, 2026, 7:20 p.m.
Created at: April 6, 2026, 12:09 p.m.