Triple
T38121847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Renclusa mountain hut |
E951957
|
entity |
| Predicate | typicalStartingTimeForAscents |
P67356
|
FINISHED |
| Object | early morning |
—
|
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: early morning | Statement: [La Renclusa mountain hut, typicalStartingTimeForAscents, early morning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalStartingTimeForAscents Context triple: [La Renclusa mountain hut, typicalStartingTimeForAscents, early morning]
-
A.
durationTypicalAscent
Indicates the typical amount of time required to complete an ascent.
-
B.
typicalSummitPushStartTime
chosen
Indicates the usual time at which climbers begin their final ascent to a summit.
-
C.
numberOfFirstAscents
Indicates the count of times an entity has been the first to successfully ascend or climb a particular route, peak, or feature.
-
D.
hasFirstRecordedAscents
Indicates that the subject is associated with the earliest known successful ascents of the specified object(s), typically in a mountaineering or climbing context.
-
E.
typicalAscentStartPoint
Indicates the usual or most common location from which an ascent or climb is begun.
- 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_69f76f07734c8190814e937e12257a78 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:21 p.m.