Triple
T22879423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ems Dispatch |
E567418
|
entity |
| Predicate | hasPlaceOfOrigin |
P3743
|
FINISHED |
| Object | Bad Ems |
—
|
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: Bad Ems | Statement: [Ems Dispatch, hasPlaceOfOrigin, Bad Ems]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Ems Context triple: [Ems Dispatch, hasPlaceOfOrigin, Bad Ems]
-
A.
Bad Ems
chosen
Bad Ems is a historic spa town in western Germany, renowned for its mineral springs and picturesque location along the Lahn River.
-
B.
Bad Grönenbach
Bad Grönenbach is a spa town in the Bavarian Allgäu region of southern Germany, known for its health resorts and picturesque rural surroundings.
-
C.
Bad Mergentheim
Bad Mergentheim is a historic spa town in the German state of Baden-Württemberg, renowned for its mineral springs and picturesque setting in the Tauber Valley.
-
D.
Bad Bibra
Bad Bibra is a small spa town in the Burgenlandkreis district of Saxony-Anhalt in central Germany, known for its rural setting and historical bathing tradition.
-
E.
Bad Ems station
Bad Ems station is a regional railway station in the spa town of Bad Ems in Rhineland-Palatinate, Germany, providing local rail connections along the Lahn Valley.
- 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_69e2458a92ec81908fc1cd5f6407d2ab |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f5b1ea481909a31a8ed6792ad04 |
completed | April 29, 2026, 3:47 a.m. |
Created at: April 17, 2026, 3:39 p.m.