Triple
T22107573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morrison Trail |
E546325
|
entity |
| Predicate | loopLength |
P147010
|
FINISHED |
| Object | approximately 12 miles |
—
|
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: approximately 12 miles | Statement: [Morrison Trail, loopLength, approximately 12 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loopLength Context triple: [Morrison Trail, loopLength, approximately 12 miles]
-
A.
loopType
Indicates the specific kind or category of loop structure or iteration pattern used in a process or control flow.
-
B.
repeatUnitLength
Indicates the length or size of a unit that is repeated within a larger pattern, sequence, or structure.
-
C.
loopsTo
Indicates that an entity has a path or connection that starts and ends at the same point, forming a loop back to itself.
-
D.
patternLength
Indicates the length or size of a recurring pattern associated with an entity or process.
-
E.
optimizedForLoopLength
Indicates that something has been adjusted or configured to achieve optimal performance or behavior specifically with respect to the length of a loop.
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1291adc74819092c7753bb6f3768d |
completed | April 28, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69e71b2ed7348190b6fa2e52f54393fb |
completed | April 21, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e7222d208c819098b12c13e31af629 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:30 p.m.