Triple
T408826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Last Frontier |
E9441
|
entity |
| Predicate | refersTo |
P37
|
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: [The Last Frontier, refersTo, Alaska]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alaska Context triple: [The Last Frontier, refersTo, 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ecbf0650819080753815ca280eec |
completed | Feb. 28, 2026, 1:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a42a12e5548190aedc6e18ef24c0ce |
completed | March 1, 2026, 11:59 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.