Triple
T2842826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rio Grande Rift |
E62508
|
entity |
| Predicate | hasMaximumBasinThickness |
P17705
|
FINISHED |
| Object | several kilometers of sediment |
—
|
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: several kilometers of sediment | Statement: [Rio Grande Rift, hasMaximumBasinThickness, several kilometers of sediment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaximumBasinThickness Context triple: [Rio Grande Rift, hasMaximumBasinThickness, several kilometers of sediment]
-
A.
hasCrustalThickness
Indicates the relationship in which an object or region possesses a specified thickness of its crust.
-
B.
hasAverageDepth
Indicates that an entity possesses a specified mean depth value, typically measured over its entire extent or area.
-
C.
maximumDepthKilometres
chosen
Indicates the greatest depth, measured in kilometers, that something reaches or extends to.
-
D.
basinType
Indicates the specific kind or classification of a basin associated with an entity (e.g., by form, function, or hydrological role).
-
E.
lakeMaximumDepth
Indicates the greatest recorded vertical distance from the lake’s surface to its deepest point.
- F. None of above.
Provenance (3 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_69ab4c3d16bc81908b3a1c98fbd287fe |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf1898748190b031a2bd2091c0c0 |
completed | March 7, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69abdd0e86808190bcefffafbd3cd441 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:01 p.m.