Triple
T9521419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naval War College (Escuela de Guerra Naval) |
E229651
|
entity |
| Predicate | mission |
P68
|
FINISHED |
| Object | to educate and train naval officers for higher responsibilities in command and staff roles |
—
|
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: to educate and train naval officers for higher responsibilities in command and staff roles | Statement: [Naval War College (Escuela de Guerra Naval), mission, to educate and train naval officers for higher responsibilities in command and staff roles]
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_69ca847870a881909d8d751a7d29da39 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9884dd5c8190b69c178cb2ac75c2 |
completed | April 1, 2026, 10:13 p.m. |
Created at: March 30, 2026, 7:59 p.m.