Triple
T15696975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umbwe Gate |
E380486
|
entity |
| Predicate | associatedRouteDifficulty |
P24163
|
FINISHED |
| Object | difficult |
—
|
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: difficult | Statement: [Umbwe Gate, associatedRouteDifficulty, difficult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedRouteDifficulty Context triple: [Umbwe Gate, associatedRouteDifficulty, difficult]
-
A.
difficultyRelativeToOtherRoutes
Indicates how the difficulty level of one route compares relative to other routes.
-
B.
hasTrailDifficulty
chosen
Indicates the level of challenge or effort required to traverse a particular trail or route.
-
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.
hasEasiestRoute
Indicates that one entity provides or represents the simplest or least difficult route or path to reach another entity or destination.
-
E.
routeBetween
Indicates that there exists a path or connection enabling travel or communication between two locations or points.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0051d639481909a10614e8f83e659 |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:44 a.m.