Triple
T722284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utah Beach |
E14643
|
entity |
| Predicate | codename |
P2980
|
FINISHED |
| Object | Utah |
E22720
|
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: Utah | Statement: [Utah Beach, codename, Utah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Utah Context triple: [Utah Beach, codename, Utah]
-
A.
Utah
chosen
Utah is a landlocked state in the western United States known for its vast deserts, distinctive red rock landscapes, and prominent national parks such as Zion and Arches.
-
B.
Idaho
Idaho is a mountainous, landlocked state in the northwestern United States known for its vast wilderness areas, outdoor recreation, and significant agricultural production, especially potatoes.
-
C.
Nevada
Nevada is a western U.S. state known for its vast deserts, legalized gambling, and the entertainment hub of Las Vegas.
-
D.
Colorado
Colorado is a landlocked U.S. state known for its Rocky Mountain landscapes, outdoor recreation, and cities like Denver and Boulder.
-
E.
Arizona
Arizona is a southwestern U.S. state known for its desert climate, the Grand Canyon, and major cities like Phoenix and Tucson.
- 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a591124c8190842e7ef18b064198 |
completed | March 1, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acddf440848190aa5019ffcedd4859 |
completed | March 8, 2026, 2:24 a.m. |
Created at: March 1, 2026, 7:37 p.m.