Triple
T8733294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leda |
E207309
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Jümme |
E666415
|
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: Jümme | Statement: [Leda, hasTributary, Jümme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jümme Context triple: [Leda, hasTributary, Jümme]
-
A.
Jümme
chosen
Jümme is a small river in Lower Saxony, Germany, known for flowing through the Leer district and contributing to the region’s network of waterways and wetlands.
-
B.
Jogne
Jogne is a river in western Switzerland that flows through the canton of Fribourg before joining the Sarine.
-
C.
Talgje
Talgje is an island in Rogaland county, Norway, known for its historic church, fertile farmland, and scenic coastal landscape.
-
D.
Jakmèl
Jakmèl is the Haitian Creole name for Jacmel, a historic coastal city in southern Haiti known for its vibrant arts scene, colonial architecture, and annual Carnival celebrations.
-
E.
Samnaun
Samnaun is a Swiss alpine village and duty-free ski resort in the Engadin valley, known for its extensive cross-border ski area shared with the Austrian resort of Ischgl.
- 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d2a26988190acfda17f232e610a |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf292d71ec819082095cb7b8b2d39c |
completed | April 3, 2026, 2:42 a.m. |
Created at: March 30, 2026, 6:37 p.m.