Triple
T663107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian Normal Route |
E12799
|
entity |
| Predicate | hasObjectiveHazard |
P1950
|
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: [Italian Normal Route, hasObjectiveHazard, crevasses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasObjectiveHazard Context triple: [Italian Normal Route, hasObjectiveHazard, crevasses]
-
A.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
B.
hasHazardSignage
Indicates that appropriate warning or hazard signs are present to alert people to potential dangers associated with the entity.
-
C.
hazardType
chosen
Indicates the specific kind or category of hazard associated with an entity or situation.
-
D.
hasClimbingHazard
Indicates that something presents a risk or danger specifically associated with climbing activities.
-
E.
hasPerception
Indicates that one entity is aware of, senses, or recognizes another entity or phenomenon.
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fd1f0ec819087003d30bbab2fa6 |
completed | March 1, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69a49d153a948190b3ccdc331ed33617 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.