Triple

T450384
Position Surface form Disambiguated ID Type / Status
Subject Anchorage E7113 entity
Predicate state P87 FINISHED
Object Alaska E890 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: Alaska | Statement: [Anchorage, state, Alaska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alaska
Context triple: [Anchorage, state, Alaska]
  • A. Alaska chosen
    Alaska is the largest and one of the most sparsely populated U.S. states, known for its vast wilderness, Arctic and sub-Arctic climate, abundant natural resources, and rich Indigenous cultures.
  • B. Hawaii
    Hawaii is a U.S. state in the central Pacific Ocean known for its volcanic islands, tropical climate, and rich Native Hawaiian culture.
  • C. Maine
    Maine is a northeastern U.S. state known for its rugged coastline, maritime history, and vast forested interior.
  • D. Montana
    Montana is a large, sparsely populated U.S. state in the northern Rocky Mountains known for its expansive wilderness, national parks like Glacier, and wide-open "Big Sky" landscapes.
  • E. Wyoming
    Wyoming is a sparsely populated U.S. state known for its vast plains, the Rocky Mountains, and iconic national parks like Yellowstone and Grand Teton.
  • 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_69a2e7e4676c81909ea0dbdecac0687c completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ef691cc8819091729eaac52c9457 completed Feb. 28, 2026, 1:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69a44cb9efc48190a161980e5506e5c8 completed March 1, 2026, 2:27 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.