Triple

T10565755
Position Surface form Disambiguated ID Type / Status
Subject CHRISTUS Health E249344 entity
Predicate city P40 FINISHED
Object Irving E37451 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: [CHRISTUS Health, city, Irving]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Irving
Context triple: [CHRISTUS Health, city, 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
    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 chosen
    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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5272ce78c8190bf3227053ef88a48 completed April 7, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9349bb7748190b5afb492e78d1128 completed April 10, 2026, 5:34 p.m.
Created at: April 6, 2026, 12:36 p.m.