Triple
T29591271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donaldson Mountain |
E754165
|
entity |
| Predicate | requiresBushwhackSections |
P194854
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Donaldson Mountain, requiresBushwhackSections, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requiresBushwhackSections Context triple: [Donaldson Mountain, requiresBushwhackSections, false]
-
A.
hasScenicSectionAt
Indicates that a route, path, or area contains a specific segment or location that is considered scenic at that point.
-
B.
hasMountainSections
Indicates that a route, area, or path includes one or more segments that pass through or are characterized by mountainous terrain.
-
C.
hasScenicSections
Indicates that a route, path, or area contains segments that are visually attractive or offer notable scenic views.
-
D.
hasBypassedSections
Indicates that certain sections within a process, route, or structure have been skipped, avoided, or not traversed as part of the overall path or execution.
-
E.
hasWalkthroughArea
Indicates that one entity includes or provides a designated area intended for walking through or passing along.
- 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69fd8ccbd4c88190b13aae0673b3c821 |
completed | May 8, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69fd8ae2227c819089546f5c3629799e |
completed | May 8, 2026, 7:04 a.m. |
| PDg | Predicate description generation | batch_69fd8ccaee848190acd59d7d643ad062 |
completed | May 8, 2026, 7:12 a.m. |
Created at: April 28, 2026, 6:14 p.m.