Triple
T3909224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Sea drainage basin |
E87280
|
entity |
| Predicate | majorRiver |
P165
|
FINISHED |
| Object | Trent |
E16617
|
NE 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: Trent | Statement: [North Sea drainage basin, majorRiver, Trent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trent Context triple: [North Sea drainage basin, majorRiver, Trent]
-
A.
Trent
chosen
The Trent is one of the principal rivers in England, flowing through the Midlands and joining the Humber estuary before reaching the North Sea.
-
B.
Son
The Son is a major south-flowing river in central and eastern India, known as a key tributary of the Ganges and an important waterway for the regions it traverses.
-
C.
Son
Son is a Japanese surname most prominently associated with Masayoshi Son, the billionaire founder and CEO of SoftBank.
-
D.
Niles
Niles is a historic former town in California, now a district of Fremont, known for its early silent film industry and railroad heritage.
-
E.
Three Rivers
Three Rivers was an Amtrak long-distance passenger train that operated between New York City and Chicago via Pittsburgh.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeed14d6d08190b74757eb9288fe4d |
completed | March 9, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51cb1b194819093b88d3f37ae51d9 |
completed | March 14, 2026, 8:30 a.m. |
Created at: March 9, 2026, 3:22 p.m.