Triple
T8745943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coleman–Deming route |
E207827
|
entity |
| Predicate | technicalRating |
P85155
|
FINISHED |
| Object | glacier travel with crevasse hazard |
—
|
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: glacier travel with crevasse hazard | Statement: [Coleman–Deming route, technicalRating, glacier travel with crevasse hazard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: technicalRating Context triple: [Coleman–Deming route, technicalRating, glacier travel with crevasse hazard]
-
A.
technicalGrade
Indicates the level or classification of technical quality, complexity, or proficiency assigned to something.
-
B.
hasRatingLevel
Indicates that an entity is associated with a particular rating level or score category.
-
C.
technologyLevel
Indicates the degree of technological advancement or sophistication associated with an entity relative to others or to a defined scale.
-
D.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
E.
technicalCrux
Indicates a key technical challenge or bottleneck that critically determines the feasibility or success of a solution or system.
- 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_69ca835bb2bc819084bb5906cb6ef7f8 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d745e0081909cab216593d5c01b |
completed | March 31, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69cc5c160dac8190b4aeb4bf0529de52 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:39 p.m.