Triple

T15575429
Position Surface form Disambiguated ID Type / Status
Subject Lampert E374356 entity
Predicate hasVariant P455 FINISHED
Object Lambert E255544 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: Lambert | Statement: [Lampert, hasVariant, Lambert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lambert
Context triple: [Lampert, hasVariant, Lambert]
  • A. Lambert chosen
    Lambert is a masculine given name of Germanic origin, historically borne by various saints, nobles, and notable figures in Europe.
  • B. Lambert Orkis
    Lambert Orkis is an American classical pianist best known for his long-standing collaborations with leading violinists and cellists, including Anne-Sophie Mutter and Mstislav Rostropovich.
  • C. Lampson
    Lampson is a surname most notably associated with American politician Nick Lampson, a former U.S. Representative from Texas.
  • D. Lemery
    Lemery is a coastal municipality in the province of Batangas in the Philippines, known for its commercial activity and proximity to Taal Lake and Volcano.
  • E. Laudon
    Laudon is a German-language surname most notably associated with the 18th-century Austrian field marshal Ernst Gideon von Laudon.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e2140388190a8df7b835eaa72ce completed April 16, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c4978ec8190a57de5d9a2ec6653 completed May 9, 2026, 3:01 p.m.
Created at: April 10, 2026, 4:10 a.m.