Triple
T35654939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lothian and Borders Fire and Rescue Service |
E1030257
|
entity |
| Predicate | jurisdiction |
P82
|
FINISHED |
| Object | Lothian and Borders region |
—
|
NE NERFINISHED |
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: Lothian and Borders region | Statement: [Lothian and Borders Fire and Rescue Service, jurisdiction, Lothian and Borders region]
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_69f76e0938088190a8f199631e97dec3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79f7760dc819093f81b4e6d4db793 |
completed | May 3, 2026, 7:18 p.m. |
Created at: May 3, 2026, 4:05 p.m.