Triple
T1149681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coniston Water |
E23646
|
entity |
| Predicate | siteOfAccident |
P26084
|
FINISHED |
| Object | death of Donald Campbell |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
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: death of Donald Campbell | Statement: [Coniston Water, siteOfAccident, death of Donald Campbell]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: siteOfAccident Context triple: [Coniston Water, siteOfAccident, death of Donald Campbell]
-
A.
accident
Indicates an unintended, unforeseen event or mishap occurring, often resulting in damage, injury, or disruption.
-
B.
accidentType
Indicates the specific category or kind of accident associated with an event or incident.
-
C.
injuryOccurredAt
Indicates that an injury took place at a specific location or during a particular event or time.
-
D.
missionAccident
Indicates that an accident or unintended harmful event occurred during the course of a mission or operation.
-
E.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
- F. None of above. chosen
Provenance (4 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bd0bed00819091d71983d787a030 |
completed | March 1, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4ee3988190ac89c5ae5b10e316 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bd0ab5f88190bb583fc63b4cc150 |
completed | March 1, 2026, 10:26 p.m. |
Created at: March 1, 2026, 7:44 p.m.