Triple

T970443
Position Surface form Disambiguated ID Type / Status
Subject Marc Tarpenning E20931 entity
Predicate residence P75 FINISHED
Object California E26 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: California | Statement: [Marc Tarpenning, residence, California]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: California
Context triple: [Marc Tarpenning, residence, California]
  • A. California, United States chosen
    California, United States is a large and populous U.S. state on the West Coast known for its diverse geography, major technology and entertainment industries, and cultural and economic influence.
  • B. Oregon
    Oregon is a U.S. state in the Pacific Northwest known for its diverse landscapes, including rugged coastline, dense forests, mountains, and high desert, as well as its environmentally conscious culture.
  • C. Nevada
    Nevada is a western U.S. state known for its vast deserts, legalized gambling, and the entertainment hub of Las Vegas.
  • D. Arizona
    Arizona is a southwestern U.S. state known for its desert climate, the Grand Canyon, and major cities like Phoenix and Tucson.
  • E. Texas
    Texas is the second-largest U.S. state by both area and population, known for its diverse landscapes, major cities like Houston and Dallas, and significant cultural and economic influence.
  • 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_69a493b33d2c81909c52c369d3ca8436 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b4497d688190b59c3a195e377080 completed March 1, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac256ee108819096092bbce2e54df5 completed March 7, 2026, 1:17 p.m.
Created at: March 1, 2026, 7:40 p.m.