Triple

T20584260
Position Surface form Disambiguated ID Type / Status
Subject Charles Taylor Sherman E505742 entity
Predicate familyName P18 FINISHED
Object Sherman 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: Sherman | Statement: [Charles Taylor Sherman, familyName, Sherman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sherman
Context triple: [Charles Taylor Sherman, familyName, Sherman]
  • A. Sherman
    Sherman is a city in north-central Texas that serves as a regional hub for commerce and transportation in the Texoma area.
  • B. Sherman
    Sherman is the bumbling yet kind-hearted scientist protagonist portrayed by Eddie Murphy in the comedy film "The Nutty Professor."
  • C. Sherman chosen
    Sherman is a surname of English origin borne by numerous notable individuals across politics, military history, and the arts.
  • D. Sherman
    Sherman is the given name of American actor Sherman Hemsley, best known for portraying George Jefferson on the television sitcoms "All in the Family" and "The Jeffersons."
  • E. Sherman
    Sherman is the curious and good-hearted young boy who travels through time with his genius dog guardian in the animated franchise "Mr. Peabody & Sherman."
  • 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_69e0b4b9669c8190b8e81fc72817d42c completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a975f098819083700593a9fa6cd0 completed April 20, 2026, 10:32 p.m.
Created at: April 16, 2026, 11:40 a.m.