Triple
T16972838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Svatava |
E411729
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Zwota (German) |
E1026307
|
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: Zwota (German) | Statement: [Svatava, hasNameInLanguage, Zwota (German)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zwota (German) Context triple: [Svatava, hasNameInLanguage, Zwota (German)]
-
A.
Zwota
chosen
Zwota is a village in the Saxon Vogtland region of Germany, known for its location near the Czech border and its tradition of musical instrument craftsmanship.
-
B.
Schlawe
Schlawe is a historic town in Pomerania, formerly in Prussia and now known as Sławno in northwestern Poland.
-
C.
Roitzsch
Roitzsch is a village-level subdivision of the town of Wurzen in the Free State of Saxony, Germany.
-
D.
Schier (German)
Schier is the German name for the Chiers, a river in Western Europe that flows through Belgium, Luxembourg, and France.
-
E.
Braunlage
Braunlage is a German town and ski resort in the Harz Mountains, known for its winter sports, hiking opportunities, and scenic natural surroundings.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0ae47f08190a13e98d20aba7f16 |
completed | April 18, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d4738fbc819099e8281ebc777091 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:31 a.m.