Triple
T8641646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maarkedal |
E204664
|
entity |
| Predicate | hasSubMunicipality |
P747
|
FINISHED |
| Object | Schorisse |
E747376
|
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: Schorisse | Statement: [Maarkedal, hasSubMunicipality, Schorisse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schorisse Context triple: [Maarkedal, hasSubMunicipality, Schorisse]
-
A.
Schorisse
chosen
Schorisse is a village in East Flanders, Belgium, that now forms part of the municipality of Maarkedal.
-
B.
Rumisberg
Rumisberg is a small Swiss municipality in the canton of Bern, situated in a rural, hilly area of the Oberaargau region.
-
C.
Murten
Murten is a historic bilingual town in the canton of Fribourg, Switzerland, known for its well-preserved medieval old town and lakeside setting on Lake Murten.
-
D.
Nideggen
Nideggen is a historic town in North Rhine-Westphalia, Germany, known for its medieval castle and scenic location in the Eifel region.
-
E.
Bürglen
Bürglen is a Swiss municipality in the alpine canton of Uri, known for its mountainous landscape and traditional rural character.
- 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_69ca834ca1c88190a11ffb0200342fac |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4795b07081908bfc9ebf35a50f07 |
completed | March 31, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf28516bd08190b69b314aea423d22 |
completed | April 3, 2026, 2:39 a.m. |
Created at: March 30, 2026, 6:28 p.m.