Triple
T5616288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shannon Pot |
E147484
|
entity |
| Predicate | hasLengthOfAssociatedRiver |
P59548
|
FINISHED |
| Object | River Shannon approximately 360 km |
—
|
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: River Shannon approximately 360 km | Statement: [Shannon Pot, hasLengthOfAssociatedRiver, River Shannon approximately 360 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLengthOfAssociatedRiver Context triple: [Shannon Pot, hasLengthOfAssociatedRiver, River Shannon approximately 360 km]
-
A.
closelyAssociatedRiver
Indicates a river that is geographically or functionally closely connected to the subject, such as flowing nearby, through, or otherwise strongly linked to it.
-
B.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
C.
waterwayLengthKilometres
chosen
Indicates the total length of a waterway, measured in kilometres.
-
D.
hasLongestRiver
Indicates that one entity possesses or contains the river that is longer than any other river associated with the compared entities.
-
E.
hasCityOnRiver
Indicates that a city is located on or along the course of a particular river.
- 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_69c00905d4588190bd967842bbcf2219 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c021da7f848190bb1cd0270ad6398f |
completed | March 22, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69c01b1b3c98819080687d18ab10a914 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:39 p.m.