Triple
T6962218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Kaweah |
E161394
|
entity |
| Predicate | difficultyRatingGeneral |
P59671
|
FINISHED |
| Object | class 3–4 routes |
—
|
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 3–4 routes | Statement: [Black Kaweah, difficultyRatingGeneral, class 3–4 routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: difficultyRatingGeneral Context triple: [Black Kaweah, difficultyRatingGeneral, class 3–4 routes]
-
A.
difficulty
Indicates the level of challenge, complexity, or effort required to perform an action, solve a problem, or achieve a particular outcome.
-
B.
difficultyClassRange
chosen
Indicates the range of difficulty classes within which an action, task, or challenge is considered to fall.
-
C.
difficultyRelativeTo
Indicates that one entity’s level of difficulty is being compared to and expressed in relation to another entity’s level of difficulty.
-
D.
difficultyGradingContext
Indicates the contextual factors or conditions that influence how difficult it is to assign a grade or evaluation to something.
-
E.
difficultySystem
Indicates a relationship where a system is characterized or classified by its level of difficulty.
- 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6daf07e3481909aa79b8e0f1b1be7 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c0b0a08190b262dfc94992994d |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:30 p.m.