Triple
T4632944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vernon |
E101458
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Ebersberg |
E251965
|
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: Ebersberg | Statement: [Vernon, hasTwinTown, Ebersberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ebersberg Context triple: [Vernon, hasTwinTown, Ebersberg]
-
A.
Ebersberg
chosen
Ebersberg is a small Bavarian town and district capital east of Munich, known for its surrounding forest and traditional Upper Bavarian character.
-
B.
Eggenfelden
Eggenfelden is a town in southeastern Germany known as a local commercial and cultural center within the region of Lower Bavaria.
-
C.
Tirschenreuth
Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
-
D.
Hettstadt
Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
-
E.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a5d0de881909baacc5b991f5b53 |
completed | March 20, 2026, 2:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb0bc858c8190b70709f5ed743ee6 |
completed | March 21, 2026, 2:52 p.m. |
Created at: March 20, 2026, 1:13 p.m.