Triple
T11165921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morungen |
E264158
|
entity |
| Predicate | hasGermanName |
P1435
|
FINISHED |
| Object | Morungen |
E264158
|
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: Morungen | Statement: [Morungen, hasGermanName, Morungen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morungen Context triple: [Morungen, hasGermanName, Morungen]
-
A.
Morungen
chosen
Morungen is the German name for the town now known as Morąg, located in northern Poland.
-
B.
Morgon
Morgon is a renowned Beaujolais cru in eastern France known for producing relatively structured, age-worthy red wines primarily from the Gamay grape.
-
C.
Maiernigg
Maiernigg is a lakeside village on Austria’s Wörthersee, best known as Gustav Mahler’s summer retreat where he composed several major works.
-
D.
Morjim
Morjim is a coastal village in North Goa, India, known for its serene beach, olive ridley turtle nesting sites, and laid-back tourism atmosphere.
-
E.
Sangin
Sangin is a town in southern Afghanistan that gained notoriety as a major battleground during the Afghan conflict, particularly involving British and U.S. forces.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e887293081909830852000d533fa |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e463945e40819087c6bdbc322a6d54 |
completed | April 19, 2026, 5:09 a.m. |
Created at: April 8, 2026, 9:29 p.m.