Triple
T27786866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | slopes of Mount Makalu |
E700983
|
entity |
| Predicate | poseRisk |
P62537
|
FINISHED |
| Object | crevasse accidents |
—
|
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: crevasse accidents | Statement: [slopes of Mount Makalu, poseRisk, crevasse accidents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: poseRisk Context triple: [slopes of Mount Makalu, poseRisk, crevasse accidents]
-
A.
riskElement
chosen
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
-
B.
AlexanderRisk
Indicates a relationship where Alexander is exposed to, associated with, or responsible for a particular risk or potential adverse outcome.
-
C.
riskType
Indicates the category or nature of risk associated with an entity, event, or relationship.
-
D.
riskTaken
Indicates that an entity has undertaken an action or decision involving exposure to potential loss, harm, or uncertainty.
-
E.
riskTheme
Indicates a relationship where an entity is associated with, categorized under, or characterized by a particular type or theme of risk.
- 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_69ef6a50d8088190acbf3dfbb06d8091 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f643ed0b7481908cf25f3afec0a61d |
completed | May 2, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f641dc8ff48190ab575d855616580c |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 5:25 p.m.