Triple

T6079733
Position Surface form Disambiguated ID Type / Status
Subject Richard M. Sherman E135491 entity
Predicate familyName P18 FINISHED
Object Sherman E558644 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: Sherman | Statement: [Richard M. Sherman, familyName, Sherman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sherman
Context triple: [Richard M. 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. The General
    The General is a famous 19th-century American steam locomotive best known for its central role in the Civil War’s Great Locomotive Chase of 1862.
  • E. The General
    The General is a science fiction novella by Isaac Asimov, part of his Foundation series, focusing on the clash between psychohistory and the military genius of General Bel Riose.
  • 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_69c0087ad31c8190ab936e0ff28614b6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0577209b88190afe5b1365cf6436d completed March 22, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11d4dc7ec8190baeede11ac27e229 completed March 23, 2026, 11 a.m.
Created at: March 22, 2026, 4:11 p.m.