Triple
T21785087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heers |
E537814
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Vorsen |
—
|
NE NERFINISHED |
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: Vorsen | Statement: [Heers, hasSubdivision, Vorsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vorsen Context triple: [Heers, hasSubdivision, Vorsen]
-
A.
Vorsen
chosen
Vorsen is a village in the municipality of Gingelom in the Belgian province of Limburg.
-
B.
Borghorst
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
-
C.
Lokstedt
Lokstedt is a district in the Eimsbüttel borough of Hamburg, Germany, known for its residential character and the presence of major broadcasting facilities.
-
D.
Lemvig
Lemvig is a small coastal town in western Denmark known for its harbor, hilly landscape, and location along the Limfjord.
-
E.
Havelberg
Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47198f881908cb0d237266c10e9 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f04630f4f08190910b9e499a4249ca |
completed | April 28, 2026, 5:31 a.m. |
Created at: April 16, 2026, 6:52 p.m.