Triple
T3490982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Marine Corps Forces Africa |
E73729
|
entity |
| Predicate | mission |
P68
|
FINISHED |
| Object | provide Marine air-ground task forces in support of U.S. military operations in Africa |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
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: provide Marine air-ground task forces in support of U.S. military operations in Africa | Statement: [United States Marine Corps Forces Africa, mission, provide Marine air-ground task forces in support of U.S. military operations in Africa]
Provenance (2 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_69ad85cca8d4819088494e9f3340fab5 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbaa720c8190af47b052cc66c225 |
completed | March 8, 2026, 6:10 p.m. |
Created at: March 8, 2026, 3:18 p.m.