Triple
T21514149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mierzeja Wiślana |
E530800
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Stegna |
—
|
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: Stegna | Statement: [Mierzeja Wiślana, hasSettlement, Stegna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stegna Context triple: [Mierzeja Wiślana, hasSettlement, Stegna]
-
A.
Stegna
chosen
Stegna is a seaside village and popular tourist resort on the Baltic coast in northern Poland.
-
B.
Stegen
Stegen is a small village in Bavaria, Germany, situated on the shores of the Ammersee and known for its lakeside recreation and boating.
-
C.
Stegny
Stegny is a residential neighborhood in the Mokotów district of Warsaw, Poland, known for its large housing estates and green spaces.
-
D.
Stallikon
Stallikon is a municipality in the canton of Zurich in Switzerland, situated in a hilly, forested area near Zurich and known for its rural character and natural landscapes.
-
E.
Stisted
Stisted is an English surname most notably associated with Henry William Stisted, a 19th-century British Army officer and colonial administrator.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea88e6fc8190a4b73b8d32dae5a8 |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:25 p.m.