Triple
T13424303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandstone Falls |
E313435
|
entity |
| Predicate | approximateDrop |
P109849
|
FINISHED |
| Object | about 10 to 25 feet in multiple ledges |
—
|
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: about 10 to 25 feet in multiple ledges | Statement: [Sandstone Falls, approximateDrop, about 10 to 25 feet in multiple ledges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateDrop Context triple: [Sandstone Falls, approximateDrop, about 10 to 25 feet in multiple ledges]
-
A.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
B.
approximateCapacity
Indicates that one entity has an estimated or rough capacity value relative to another or to a specified measure.
-
C.
dropCount
Indicates the number of times an entity has been dropped or caused to drop something.
-
D.
holdsApproximatelyFor
Indicates that a condition, relation, or value is valid only to an approximate degree or within a tolerance, rather than holding exactly.
-
E.
killedApproximate
Indicates that one entity caused the death of another, but the information about this killing is uncertain, estimated, or not known with exact precision.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed066408190a416880affd8416e |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:39 p.m.