Triple

T12057843
Position Surface form Disambiguated ID Type / Status
Subject K. C. Irving E287088 entity
Predicate familyName P18 FINISHED
Object Irving E6973 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: Irving | Statement: [K. C. Irving, familyName, Irving]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Irving
Context triple: [K. C. Irving, familyName, Irving]
  • A. Irving
    Irving is a masculine given name of English origin that gained prominence in the late 19th and early 20th centuries, borne by figures such as film producer Irving Thalberg and writer Washington Irving.
  • B. Irving
    Irving is the Allied reporting name for the Japanese Nakajima J1N twin-engine night fighter used during World War II.
  • C. Irving chosen
    Irving is a surname most famously associated with Washington Irving, the early 19th-century American author of classics like "Rip Van Winkle" and "The Legend of Sleepy Hollow."
  • D. Irving
    Irving is a major suburban city in the Dallas–Fort Worth metropolitan area known for its diverse population and significant business and transportation hubs.
  • E. Irving, Texas
    Irving, Texas is a major city in the Dallas–Fort Worth metropolitan area known for its corporate presence, transportation hubs, and role as a center for business and sports administration.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9043bf0ec8190a51ef2641808320c completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f651641c8190bfd1d4d228a36209 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:47 p.m.