Triple
T11174249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Preux |
E264364
|
entity |
| Predicate | travelsTo |
P21947
|
FINISHED |
| Object | Clarens |
E33305
|
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: Clarens | Statement: [Saint-Preux, travelsTo, Clarens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clarens Context triple: [Saint-Preux, travelsTo, Clarens]
-
A.
Clarens
Clarens is a picturesque lakeside locality in the Swiss Riviera region on the shores of Lake Geneva, known for its scenic views and mild climate.
-
B.
Groblersdal
Groblersdal is a town in South Africa’s Limpopo province known as an important agricultural center, particularly for irrigation-based farming.
-
C.
Clarens, Switzerland
chosen
Clarens, Switzerland is a picturesque lakeside resort village on Lake Geneva, known for its scenic views of the Alps and its association with notable historical figures.
-
D.
Colesberg
Colesberg is a small historic town in South Africa’s Northern Cape, known as a key stopover on the N1 highway and a gateway to the semi-arid Karoo region.
-
E.
Stormberg
Stormberg is a mountainous region in South Africa known for its high plateaus, rugged terrain, and significant geological and historical features.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e897774c819088ebc7231cebfba6 |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e463c03a948190b0f40f657180c9bf |
completed | April 19, 2026, 5:10 a.m. |
Created at: April 8, 2026, 9:29 p.m.