Triple
T2390836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohrungen |
E48937
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Morąg |
E220539
|
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: Morąg | Statement: [Mohrungen, hasAlternativeName, Morąg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morąg Context triple: [Mohrungen, hasAlternativeName, Morąg]
-
A.
Morąg
chosen
Morąg is a small historic town in northern Poland known for its lakeside surroundings and location within the Warmian-Masurian Voivodeship.
-
B.
Morskie Oko
Morskie Oko is a famous glacial lake in the Tatra Mountains of southern Poland, renowned for its scenic alpine setting and popularity as a hiking destination.
-
C.
Baltus
Baltus is a fictional character best known as the wealthy farmer and father of Katrina Van Tassel in Washington Irving’s short story “The Legend of Sleepy Hollow.”
-
D.
Zalewo
Zalewo is a small town in northern Poland, situated in the Warmian-Masurian Voivodeship known for its lakes and natural landscapes.
-
E.
Mór
Mór is a town in central Hungary known for its wine production and location between the Vértes and Bakony hills.
- 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_69a88aa5f63081908d07fd302029fcbd |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc87457388190822d5506327db8f2 |
completed | March 7, 2026, 6:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef09854fc8190bab0415e3815a920 |
completed | March 9, 2026, 4:08 p.m. |
Created at: March 4, 2026, 7:57 p.m.