Triple

T5962936
Position Surface form Disambiguated ID Type / Status
Subject Joshua Lyman E132681 entity
Predicate closeColleague P11349 FINISHED
Object Toby Ziegler E40003 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: Toby Ziegler | Statement: [Joshua Lyman, closeColleague, Toby Ziegler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toby Ziegler
Context triple: [Joshua Lyman, closeColleague, Toby Ziegler]
  • A. Toby Ziegler chosen
    Toby Ziegler is a central fictional character on the television series "The West Wing," serving as the White House Communications Director known for his sharp intellect, moral conviction, and often dour demeanor.
  • B. Toby Pohlen
    Toby Pohlen is a member of the team at xAI, the artificial intelligence company founded by Elon Musk.
  • C. Joseph Zumstein
    Joseph Zumstein was a 19th-century Swiss mountaineer and surveyor known for his pioneering ascents and contributions to Alpine exploration.
  • D. Toby Halbrooks
    Toby Halbrooks is an American filmmaker and screenwriter known for his frequent collaborations with director David Lowery on independent and studio films.
  • E. Garrett Gruener
    Garrett Gruener is an American entrepreneur and venture capitalist best known as a co-founder of the early internet search engine Ask Jeeves.
  • 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_69c0086c2364819091e9fe2f58fa2517 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a00e444819087f9df62263e83dc completed March 22, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3ee20648190badedf60a8bc938b completed March 23, 2026, 6:55 a.m.
Created at: March 22, 2026, 4:03 p.m.