Triple

T18254713
Position Surface form Disambiguated ID Type / Status
Subject Cyan Banister E437193 entity
Predicate spouse P13 FINISHED
Object Scott Banister 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: Scott Banister | Statement: [Cyan Banister, spouse, Scott Banister]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scott Banister
Context triple: [Cyan Banister, spouse, Scott Banister]
  • A. Scott Banister chosen
    Scott Banister is an American entrepreneur and angel investor known for co-founding IronPort and early involvement with companies like PayPal and Facebook.
  • B. Michael Bannister
    Michael Bannister is a musician best known as a member of the Scottish indie rock supergroup Reindeer Section.
  • C. Christopher Benstead
    Christopher Benstead is a British composer and music editor known for his film scores and sound work on major movies, including collaborations with director Guy Ritchie.
  • D. Howard Bannister
    Howard Bannister is the mild-mannered, musicologist protagonist played by Ryan O'Neal in the screwball comedy film "What's Up, Doc?".
  • E. Lee Stack
    Lee Stack was a British Army officer and colonial administrator who served as Governor-General of the Anglo-Egyptian Sudan and Sirdar of the Egyptian Army in the early 20th century.
  • 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4fd84b3a481908bbc1a5e5034d397 completed April 19, 2026, 4:06 p.m.
Created at: April 10, 2026, 10:33 a.m.