Triple
T2201198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mississippi River basin |
E50492
|
entity |
| Predicate | drainagePercentageOfUS |
P36927
|
FINISHED |
| Object | about 41 percent |
—
|
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 41 percent | Statement: [Mississippi River basin, drainagePercentageOfUS, about 41 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drainagePercentageOfUS Context triple: [Mississippi River basin, drainagePercentageOfUS, about 41 percent]
-
A.
areaWaterPercentage
Indicates the proportion of an entity’s total area that is covered by water, typically expressed as a percentage.
-
B.
drainageAreaApprox
Indicates that one entity has an approximate drainage area measured or characterized by the other entity.
-
C.
drainageType
Indicates the kind or classification of drainage associated with or applied to an entity (e.g., how water is removed or flows from it).
-
D.
drainsInto
Indicates that one entity serves as a source or conduit whose contents or flow are directed into another entity.
-
E.
dischargeRankInNorthAmerica
Indicates the relative ranking of an entity based on its discharge (e.g., flow or output) compared to others within North America.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfa1b41c8190b0f7467d0dcdfbcd |
completed | March 7, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69abbda706f4819094de73e1d1d1f539 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbf35c994819088a093c412931de4 |
completed | March 7, 2026, 6:01 a.m. |
Created at: March 4, 2026, 7:46 p.m.