Triple
T2522665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WWF |
E55558
|
entity |
| Predicate | foundedIn |
P41
|
FINISHED |
| Object | Morges, Switzerland |
E230089
|
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: Morges, Switzerland | Statement: [WWF, foundedIn, Morges, Switzerland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morges, Switzerland Context triple: [WWF, foundedIn, Morges, Switzerland]
-
A.
Morges
chosen
Morges is a Swiss town on the shores of Lake Geneva that historically hosted the founding of the World Wildlife Fund and serves as a local cultural and economic center in the canton of Vaud.
-
B.
La Sarraz, Switzerland
La Sarraz, Switzerland is a small historic town in the canton of Vaud known for its medieval castle and its role in early 20th-century modern architecture movements.
-
C.
Engelberg, Switzerland
Engelberg, Switzerland is a mountain resort village in the Swiss canton of Obwalden, renowned for its skiing, hiking, and alpine scenery.
-
D.
Gstaad
Gstaad is an upscale Swiss alpine resort village renowned for its luxury hotels, skiing, and exclusive social scene.
-
E.
Aigle, Switzerland
Aigle, Switzerland is a small town in the canton of Vaud known as an international hub for professional cycling and sports administration.
- 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd23895348190bb4dad6d7174893a |
completed | March 7, 2026, 7:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2ba96a0c819091efd6d4ccf95ea5 |
completed | March 9, 2026, 8:20 p.m. |
Created at: March 6, 2026, 9:46 p.m.