Triple
T16898334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frendo Spur |
E424367
|
entity |
| Predicate | difficultyFrenchAlpine |
P123916
|
FINISHED |
| Object | D+ |
—
|
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: D+ | Statement: [Frendo Spur, difficultyFrenchAlpine, D+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: difficultyFrenchAlpine Context triple: [Frendo Spur, difficultyFrenchAlpine, D+]
-
A.
durationTypicalAscent
Indicates the typical amount of time required to complete an ascent.
-
B.
climbingDifficultyContext
chosen
Indicates the contextual conditions or factors (such as environment, route type, or situation) under which a climbing difficulty assessment applies.
-
C.
typeOfClimb
Indicates the specific style or category of climbing activity associated with a climb (e.g., bouldering, sport, trad).
-
D.
skiAreaAltitudeRange_m
Indicates the range of altitudes, in meters, over which a ski area extends.
-
E.
altitudeCategory
Indicates the classification of something based on its height or elevation relative to a reference level (e.g., low, medium, high altitude).
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8d98c308190bcc0adc7797d1f40 |
completed | April 18, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69e32b9489408190bcb2ede567ff5bf9 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:29 a.m.