Triple
T13627568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A29 road |
E325624
|
entity |
| Predicate | crosses |
P416
|
FINISHED |
| Object | River Arun |
E194056
|
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: River Arun | Statement: [A29 road, crosses, River Arun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: River Arun Context triple: [A29 road, crosses, River Arun]
-
A.
River Arun
chosen
The River Arun is a major river in West Sussex, England, flowing from the South Downs to the English Channel and historically important for navigation and trade.
-
B.
Lez River
The Lez River is a short coastal river in southern France that flows through the city of Montpellier before emptying into the Mediterranean Sea.
-
C.
Aar River
The Aar River is a small river in western Germany that flows through the Taunus region and passes spa towns such as Bad Schwalbach before joining the Lahn.
-
D.
River Whye
River Whye is a fictional river in Stephen King’s Dark Tower universe, flowing through the central realm known as Mid-World.
-
E.
River Dart
The River Dart is a scenic river in Devon, England, known for flowing through Dartmoor to the English Channel and for its historic maritime and boating connections, including the naval town of Dartmouth.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbe9d803481908101def32817b0eb |
completed | April 12, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1b4ae588190b293c71312ee4037 |
completed | May 6, 2026, 8:16 p.m. |
Created at: April 9, 2026, 9:51 p.m.