Triple
T35378292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paschal Donohoe |
E1022574
|
entity |
| Predicate | positionHeld |
P8
|
FINISHED |
| Object | Minister for Public Expenditure and Reform of Ireland |
—
|
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: Minister for Public Expenditure and Reform of Ireland | Statement: [Paschal Donohoe, positionHeld, Minister for Public Expenditure and Reform of Ireland]
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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79466e77081909fa053e861e254cc |
completed | May 3, 2026, 6:31 p.m. |
Created at: May 3, 2026, 4:03 p.m.