Triple
T2257156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lower Yosemite Fall Trail |
E49752
|
entity |
| Predicate | hasLoopDirectionOptions |
P36771
|
FINISHED |
| Object | clockwise or counterclockwise |
—
|
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: clockwise or counterclockwise | Statement: [Lower Yosemite Fall Trail, hasLoopDirectionOptions, clockwise or counterclockwise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoopDirectionOptions Context triple: [Lower Yosemite Fall Trail, hasLoopDirectionOptions, clockwise or counterclockwise]
-
A.
hasCountingDirection
Indicates the direction or order in which counting or enumeration proceeds between related entities.
-
B.
hasDirectionType
Indicates that something possesses or is associated with a specific type or category of direction.
-
C.
loopType
Indicates the specific kind or category of loop structure or iteration pattern used in a process or control flow.
-
D.
hasRouteDirection
Indicates that a specified route is associated with a particular travel direction (e.g., inbound, outbound, northbound).
-
E.
circuitDirection
Indicates the orientation or flow direction of a circuit or circuit path relative to its components or layout.
- 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_69a88aaa9250819095e127d0d77e8a32 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc1570dc88190bb2b17ed4c25dbb5 |
completed | March 7, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69abbdb34c148190b51e99f540f97204 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbe86dbcc81908c72793af8fe2a4d |
completed | March 7, 2026, 5:58 a.m. |
Created at: March 4, 2026, 7:47 p.m.