Triple
T2229329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Class A airspace |
E48727
|
entity |
| Predicate | verticalExtent |
P10733
|
FINISHED |
| Object | from 18,000 feet MSL up to and including FL600 |
—
|
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: from 18,000 feet MSL up to and including FL600 | Statement: [Class A airspace, verticalExtent, from 18,000 feet MSL up to and including FL600]
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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0685b688190857a76c1043f4b92 |
completed | March 7, 2026, 6:06 a.m. |
Created at: March 4, 2026, 7:47 p.m.