Triple
T16734351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denali north-side climbing routes |
E406677
|
entity |
| Predicate | haveTypicalObjectiveHazards |
P63246
|
FINISHED |
| Object | crevasses |
—
|
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: crevasses | Statement: [Denali north-side climbing routes, haveTypicalObjectiveHazards, crevasses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveTypicalObjectiveHazards Context triple: [Denali north-side climbing routes, haveTypicalObjectiveHazards, crevasses]
-
A.
hasObjectiveHazards
chosen
Indicates that an entity is associated with concrete, externally verifiable dangers or risks.
-
B.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
C.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
D.
hazardScope
Indicates the range or extent within which a particular hazard is relevant, applicable, or has effect.
-
E.
hasHazardLevel
Indicates that an entity is associated with a specified degree or category of risk or danger.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c38c9cc8190a3220cc3684388dc |
completed | April 18, 2026, 2:59 p.m. |
| PD | Predicate disambiguation | batch_69e319c807788190901250ab6e0ca55f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:20 a.m.