Triple
T8931281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hesse-Bessungen |
E212658
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Bessungen |
E766287
|
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: Bessungen | Statement: [Hesse-Bessungen, namedAfter, Bessungen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bessungen Context triple: [Hesse-Bessungen, namedAfter, Bessungen]
-
A.
Bessungen
chosen
Bessungen is a historic district of the city of Darmstadt in the German state of Hesse, known for its traditional architecture and village-like character.
-
B.
Schonungen
Schonungen is a municipality in the Lower Franconia region of Bavaria, Germany, situated near the city of Schweinfurt along the Main River.
-
C.
Kehrsatz
Kehrsatz is a municipality in the canton of Bern, Switzerland, situated just south of the city of Bern within its metropolitan region.
-
D.
Bett
Bett is a given name, typically used as a short form or variant of names like Bette, Elizabeth, or Bettina.
-
E.
Maiernigg
Maiernigg is a lakeside village on Austria’s Wörthersee, best known as Gustav Mahler’s summer retreat where he composed several major works.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc668cdc0c8190b908fd23cbdef534 |
completed | April 1, 2026, 12:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc93587b081908e23c2a8c01b9516 |
completed | April 3, 2026, 2:05 p.m. |
Created at: March 30, 2026, 6:57 p.m.