Triple

T9657003
Position Surface form Disambiguated ID Type / Status
Subject Bean E233483 entity
Predicate nickname P55 FINISHED
Object Bean E255978 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: Bean | Statement: [Bean, nickname, Bean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bean
Context triple: [Bean, nickname, Bean]
  • A. Bean chosen
    Bean is a common English surname of Old English origin, associated with various notable individuals including the actor Sean Bean.
  • B. Bean
    Bean is a small village and civil parish in the borough of Dartford in north-west Kent, England.
  • C. Bean
    Bean is a 1997 British-American comedy film based on Rowan Atkinson’s Mr. Bean character, following his chaotic misadventures in the United States.
  • D. Bean
    Bean is the famous jazz saxophonist Coleman Hawkins, a pioneering tenor sax player whose rich tone and improvisational style helped define early jazz.
  • E. JavaBeans
    JavaBeans is a reusable software component model for the Java platform that defines conventions for building modular, configurable Java classes, often used in visual development environments.
  • 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_69ca848c1ba88190b84b410cd14627fc completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9bdd5c0c8190a6c82a1609454d1b completed April 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69d190eec94c81909ede398926141f89 completed April 4, 2026, 10:30 p.m.
Created at: March 30, 2026, 8:14 p.m.