Triple
T20563072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1922 British Mount Everest expedition |
E504892
|
entity |
| Predicate | causeOfMainAccident |
P1788
|
FINISHED |
| Object | avalanche |
—
|
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: avalanche | Statement: [1922 British Mount Everest expedition, causeOfMainAccident, avalanche]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfMainAccident Context triple: [1922 British Mount Everest expedition, causeOfMainAccident, avalanche]
-
A.
causedAccident
Indicates that one entity is responsible for bringing about or initiating an accident involving another entity or situation.
-
B.
accidentType
chosen
Indicates the specific category or kind of accident associated with an event or incident.
-
C.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
-
D.
fatalAccident
Indicates that an accident resulted in at least one death.
-
E.
accident
Indicates an unintended, unforeseen event or mishap occurring, often resulting in damage, injury, or disruption.
- F. None of above.
Provenance (3 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a79f906c819081163de9649ccb17 |
completed | April 20, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69e59ff0116c8190a163ff28ed01430a |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:39 a.m.