Triple
T31909948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kodachrome Basin State Park |
E814652
|
entity |
| Predicate | numberOfSandPipes |
P203311
|
FINISHED |
| Object | over 60 |
—
|
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: over 60 | Statement: [Kodachrome Basin State Park, numberOfSandPipes, over 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSandPipes Context triple: [Kodachrome Basin State Park, numberOfSandPipes, over 60]
-
A.
numberOfOrganPipes
Indicates the quantitative relationship specifying how many organ pipes are associated with a given organ or organ-related entity.
-
B.
approximateNumberOfPipes
Indicates that the relationship specifies an estimated count of pipes associated with an entity.
-
C.
numberOfTubes
Indicates the quantity of tubes associated with or contained by a given entity.
-
D.
spillwayCount
Indicates the number of spillways associated with or present in a given structure or location.
-
E.
numberOfPiers
Indicates the quantity of piers associated with or present in a given structure, location, or context.
- 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_69f348f109d88190b5005372c53d2fcd |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a01531add1c8190b51add7bb046e2cb |
completed | May 11, 2026, 3:55 a.m. |
| PD | Predicate disambiguation | batch_6a014fef3d8c81909b509d51d0c4cdc7 |
completed | May 11, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_6a01531a3a4c8190ac8cb040cc36e96b |
completed | May 11, 2026, 3:55 a.m. |
Created at: May 1, 2026, 12:01 a.m.