Triple

T4651207
Position Surface form Disambiguated ID Type / Status
Subject Language Models are Few-Shot Learners E102297 entity
Predicate author P4 FINISHED
Object Eric Sigler E525096 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: Eric Sigler | Statement: [Language Models are Few-Shot Learners, author, Eric Sigler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eric Sigler
Context triple: [Language Models are Few-Shot Learners, author, Eric Sigler]
  • A. Eric Sigler chosen
    Eric Sigler is a researcher known for co-authoring influential work in artificial intelligence and machine learning alongside Tom B. Brown.
  • B. Eric Jager
    Eric Jager is an American medievalist and author best known for his historical narrative "The Last Duel," which recounts a famous 14th-century French trial by combat.
  • C. Mark Okerstrom
    Mark Okerstrom is a Canadian business executive best known for serving as the former CEO of Expedia Group.
  • D. Eric Pleskow
    Eric Pleskow was an Austrian-born American film executive and producer best known for leading major studios and co-founding the influential independent film company Orion Pictures.
  • E. Eric Schoffstall
    Eric Schoffstall is a software developer best known for creating Gulp, a popular JavaScript-based task runner used in web development build workflows.
  • 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_69bf88de71b481908ac7b13a3d1538db completed March 22, 2026, 6:14 a.m.
Created at: March 20, 2026, 1:14 p.m.