Triple

T10985532
Position Surface form Disambiguated ID Type / Status
Subject Colin Irving E259618 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: [Colin Irving, familyName, Irving]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Irving
Context triple: [Colin 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d787b2e4a88190a81504eee77e2298 completed April 9, 2026, 11:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69e344d860b08190a035570191c54d7c completed April 18, 2026, 8:46 a.m.
Created at: April 8, 2026, 9:24 p.m.