Triple

T4651199
Position Surface form Disambiguated ID Type / Status
Subject Language Models are Few-Shot Learners E102297 entity
Predicate author P4 FINISHED
Object Tom Henighan E461713 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: Tom Henighan | Statement: [Language Models are Few-Shot Learners, author, Tom Henighan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Henighan
Context triple: [Language Models are Few-Shot Learners, author, Tom Henighan]
  • A. Tom Henighan chosen
    Tom Henighan is a researcher and co-author known for his work in large-scale language models and AI, including contributions to influential OpenAI publications.
  • B. Jack McHale
    Jack McHale is a relatively obscure individual known primarily as a namesake referenced in records of notable bearers of the surname McHale.
  • C. Tom Hickey
    Tom Hickey was an Irish actor known for his extensive work in theatre, film, and television, particularly in Ireland.
  • D. Eddie Cahill
    Eddie Cahill is an American actor best known for his role as Detective Don Flack on the television series CSI: NY.
  • E. Max O’Hara
    Max O’Hara is a fast-talking, ambitious showman and nightclub promoter who brings the giant gorilla Joe to Hollywood in the 1949 adventure film "Mighty Joe Young."
  • 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_69bd43d71a308190afea7280841b0de8 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd630343f88190954d19fcd18a5864 completed March 20, 2026, 3:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69be1040dbdc8190b9ab7b0b58bca308 completed March 21, 2026, 3:28 a.m.
Created at: March 20, 2026, 1:14 p.m.