Triple
T16562596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Missouri Mountain |
E402376
|
entity |
| Predicate | hasDifficultyClass |
P124063
|
FINISHED |
| Object | Class 2 (standard hiking route) |
—
|
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: Class 2 (standard hiking route) | Statement: [Missouri Mountain, hasDifficultyClass, Class 2 (standard hiking route)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDifficultyClass Context triple: [Missouri Mountain, hasDifficultyClass, Class 2 (standard hiking route)]
-
A.
hasDifficultyContext
Indicates that something’s difficulty is defined, interpreted, or constrained within a particular situational or contextual framework.
-
B.
hasDifficultyEffect
Indicates that one entity causes a change in the difficulty level or challenge associated with another entity or activity.
-
C.
difficultyClassRange
Indicates the range of difficulty classes within which an action, task, or challenge is considered to fall.
-
D.
hasDifficultyWith
Indicates that one entity experiences problems, challenges, or lack of proficiency in dealing with, understanding, or performing something related to another entity.
-
E.
hasMeasurementDifficulty
Indicates that performing a measurement on something is challenging or problematic in some way.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3576f757881909bfc6611361ed16d |
completed | April 18, 2026, 10:05 a.m. |
| PD | Predicate disambiguation | batch_69e296a47b7481909d9958158510c806 |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7f97e548190a474691a152bd8e8 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:15 a.m.