Triple
T8144930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pannerdens Kanaal |
E190184
|
entity |
| Predicate | mouthRiver |
P4359
|
FINISHED |
| Object | Waal |
E26512
|
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: Waal | Statement: [Pannerdens Kanaal, mouthRiver, Waal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waal Context triple: [Pannerdens Kanaal, mouthRiver, Waal]
-
A.
Waal
chosen
The Waal is a major distributary branch of the Rhine River in the Netherlands, serving as an important waterway for shipping and part of the country’s main river system.
-
B.
Dieuze
Dieuze is a small commune in northeastern France, located in the Moselle department in the historical region of Lorraine.
-
C.
Geul River
The Geul River is a small, winding river in the southeastern Netherlands and eastern Belgium, known for its scenic valleys, historic watermills, and role in shaping the hilly landscape of South Limburg.
-
D.
Geul
The Geul is a small river in the southeastern Netherlands and eastern Belgium, known for flowing through the hilly Limburg landscape and picturesque villages before joining the Meuse.
-
E.
Niederscheld
Niederscheld is a village and district of the town of Dillenburg in the Lahn-Dill-Kreis of Hesse, Germany.
- 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_69ca82be7ba8819087de0147e9292c83 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4445f1948190b8d319b60dd47f65 |
completed | March 31, 2026, 3:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6ca1110c8190b72a2a573ddab06d |
completed | April 2, 2026, 1:18 p.m. |
Created at: March 30, 2026, 5:36 p.m.