Triple

T18724459
Position Surface form Disambiguated ID Type / Status
Subject Language Models are Few-Shot Learners E457860 entity
Predicate author P4 FINISHED
Object Benjamin Mann — 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: Benjamin Mann | Statement: [Language Models are Few-Shot Learners, author, Benjamin Mann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Benjamin Mann
Context triple: [Language Models are Few-Shot Learners, author, Benjamin Mann]
  • A. Benjamin Mann chosen
    Benjamin Mann is an AI researcher and engineer known for co-authoring influential work on large language models at OpenAI.
  • B. Henry Deringer
    Henry Deringer was a 19th-century American gunsmith best known for designing the small, easily concealable pocket pistols that became widely popular and lent their name (via a misspelling) to the term "derringer."
  • C. Henry Harvey
    Henry Harvey is a fictional character portrayed by actor Dana Andrews, likely in a mid-20th-century film or television production.
  • D. Henry Harvey
    Henry Harvey was a British Royal Navy officer and admiral who served prominently during the late 18th century, particularly in Caribbean campaigns against French and Spanish forces.
  • E. Daniel Mann
    Daniel Mann was an American film and theater director known for his work on mid-20th-century Hollywood dramas such as "Come Back, Little Sheba" and "Butterfield 8."
  • 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_69d8d393ba9c8190a8b03b04ddbb0a09 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e56d72d2c4819080b0d31860976b5e completed April 20, 2026, 12:04 a.m.
Created at: April 10, 2026, 11:50 a.m.