Triple

T8325751
Position Surface form Disambiguated ID Type / Status
Subject Leonard Susskind E194947 entity
Predicate givenName P17 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: [Leonard Susskind, givenName, Leonard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leonard
Context triple: [Leonard Susskind, givenName, 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. Leonard Graves
    Leonard Graves was an American actor and voice artist best known for narrating the acclaimed World War II documentary television series "Victory at Sea."
  • 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_69ca82e7a8a88190a32bb5cc0feb012d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f7fba688190b696593dfb2cde5d completed March 31, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95b22afc81909c867d83a1744139 completed April 1, 2026, 10:01 p.m.
Created at: March 30, 2026, 5:56 p.m.