Triple
T17316150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ameland |
E420428
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Buren |
E328878
|
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: Buren | Statement: [Ameland, hasSettlement, Buren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buren Context triple: [Ameland, hasSettlement, Buren]
-
A.
Buren
Buren is the entomologist who formally described the invasive red imported fire ant species Solenopsis invicta.
-
B.
Buren
chosen
Buren is a historic Dutch town in the province of Gelderland, known for its ties to the Dutch royal family and its well-preserved medieval character.
-
C.
Peynet
Peynet is the surname of French illustrator Raymond Peynet, best known for his romantic "lovers" drawings that became iconic in mid-20th-century France.
-
D.
Baulmes
Baulmes is a Swiss village and municipality in the canton of Vaud, situated near the Jura Mountains and known for its scenic rural landscape.
-
E.
Bezannes
Bezannes is a commune in northeastern France near Reims, known for hosting the Champagne-Ardenne TGV high-speed railway station.
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4399d2fcc81909916302f141e236b |
completed | April 19, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0180e8cfd88190a105b778e5b9e864 |
completed | May 11, 2026, 7:10 a.m. |
Created at: April 10, 2026, 5:43 a.m.