Triple
T10793416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Champ-du-Moulin |
E254640
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Boudry |
E136315
|
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: Boudry | Statement: [Champ-du-Moulin, locatedNear, Boudry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boudry Context triple: [Champ-du-Moulin, locatedNear, Boudry]
-
A.
Boudry
chosen
Boudry is a municipality in the canton of Neuchâtel in western Switzerland, known as a historic town near Lake Neuchâtel.
-
B.
Wavre
Wavre is a town in central Belgium that serves as the capital of Walloon Brabant and is known for hosting the Walibi Belgium amusement park.
-
C.
Tessenderlo
Tessenderlo is a municipality in the Belgian province of Limburg, known for its chemical industry and location near the Albert Canal.
-
D.
Blegny
Blegny is a municipality in eastern Belgium known for its historic coal mining heritage and rural character.
-
E.
Bottendorf
Bottendorf is a locality in the German state of Thuringia that historically existed within the German Empire.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732f878648190be5e25c56a7511cf |
completed | April 9, 2026, 5:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb0c85d288190b13b1bc66921332c |
completed | April 14, 2026, 9:25 p.m. |
Created at: April 8, 2026, 9:17 p.m.