Triple
T10215264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hubert van Eyck |
E242424
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Maaseik |
E236095
|
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: Maaseik | Statement: [Hubert van Eyck, placeOfBirth, Maaseik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maaseik Context triple: [Hubert van Eyck, placeOfBirth, Maaseik]
-
A.
Maaseik
chosen
Maaseik is a historic town in the Belgian province of Limburg, known as the birthplace of the Early Netherlandish painter Jan van Eyck.
-
B.
Maasmechelen
Maasmechelen is a municipality in the Belgian province of Limburg, known for its proximity to the Meuse River and the popular Maasmechelen Village outlet shopping center.
-
C.
La Meije
La Meije is a prominent and rugged peak in the French Alps, renowned among mountaineers for its dramatic profile and challenging climbing routes.
-
D.
Namsskogan
Namsskogan is a sparsely populated inland municipality in Trøndelag county, Norway, known for its vast forests, wildlife, and outdoor recreation opportunities.
-
E.
Valberg
Valberg is a popular ski resort village in the southern French Alps known for its family-friendly slopes and sunny Mediterranean-alpine climate.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa273bdc8190bc4cf67a7923cebc |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d652f1ffb88190986ea53749fc5e03 |
completed | April 8, 2026, 1:06 p.m. |
Created at: April 6, 2026, 11:04 a.m.