Triple

T4628954
Position Surface form Disambiguated ID Type / Status
Subject Mortimer L. Schiff E101166 entity
Predicate givenName P17 FINISHED
Object Mortimer E425816 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: Mortimer | Statement: [Mortimer L. Schiff, givenName, Mortimer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mortimer
Context triple: [Mortimer L. Schiff, givenName, Mortimer]
  • A. Mortimer
    Mortimer is a village and civil parish in West Berkshire, England, known for its rural character and commuter links to nearby Reading.
  • B. Mortimer chosen
    Mortimer is a masculine given name of Old French origin, historically associated with English nobility and later borne by various notable figures in philosophy, literature, and the arts.
  • C. Fitzwalter
    Fitzwalter is an English noble family name historically associated with medieval barons and landholders.
  • D. Nevill
    Nevill is a given name most notably borne by British physicist and Nobel laureate Sir Nevill Mott.
  • E. Crispin Bonham-Carter
    Crispin Bonham-Carter is a British actor and theatre director best known for playing Mr. Bingley in the 1995 BBC adaptation of "Pride and Prejudice."
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a300e6081909fa9f504aada33ea completed March 20, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfab4f4808190920e420f566dec9b completed March 21, 2026, 1:56 a.m.
Created at: March 20, 2026, 1:13 p.m.