Triple
T11787345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merano |
E280303
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Meran |
E280303
|
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: Meran | Statement: [Merano, alsoKnownAs, Meran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meran Context triple: [Merano, alsoKnownAs, Meran]
-
A.
Merano
chosen
Merano is a historic spa and resort town in northern Italy known for its mild climate, Alpine scenery, and blend of Italian and Austrian cultural influences.
-
B.
Villach
Villach is a historic city in southern Austria known for its Alpine setting, thermal spas, and role as a regional transport and cultural hub.
-
C.
Mendrisio
Mendrisio is a district and town in the canton of Ticino in southern Switzerland, known for its historic center and proximity to the Italian border.
-
D.
Klagenfurt
Klagenfurt is the capital city of the Austrian state of Carinthia, known for its historic old town and proximity to Lake Wörthersee.
-
E.
Bolzano
Bolzano was an Italian Zara-class heavy cruiser of the Regia Marina that served during World War II in the Mediterranean Sea.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a586803481909af0032c35ca6e51 |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f166c735008190a73dd74dbcddd182 |
completed | April 29, 2026, 2:02 a.m. |
Created at: April 8, 2026, 9:42 p.m.