Triple
T12019390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dyle |
E286107
|
entity |
| Predicate | confluenceWith |
P2416
|
FINISHED |
| Object | Nete |
E442252
|
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: Nete | Statement: [Dyle, confluenceWith, Nete]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nete Context triple: [Dyle, confluenceWith, Nete]
-
A.
Nete
chosen
The Nete is a river in Belgium that flows through the Flemish region and serves as one of the main tributaries forming the Rupel River.
-
B.
Nese
Nese is an endangered Oceanic language spoken by a small community on the island of Malakula in Vanuatu.
-
C.
Nesiota
Nesiota is a small, likely extinct genus of flowering plants in the buckthorn family Rhamnaceae, historically known from the South Atlantic island of St. Helena.
-
D.
Niele
Niele is a feminine given name most notably borne by Niele Ivey, an American basketball coach and former WNBA player.
-
E.
Netersel
Netersel is a small village in the Dutch province of North Brabant, known for its rural character and location within the municipality of Bladel.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903dabf2c819084dcaa05ae0a6018 |
completed | April 10, 2026, 2:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48b53cd08819084a9335449844f12 |
completed | May 1, 2026, 11:15 a.m. |
Created at: April 8, 2026, 9:47 p.m.