Triple
T16057862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maroggia |
E389528
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Capolago |
E81144
|
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: Capolago | Statement: [Maroggia, borders, Capolago]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Capolago Context triple: [Maroggia, borders, Capolago]
-
A.
Capolago
chosen
Capolago is a village in the canton of Ticino in southern Switzerland, located on the shore of Lake Lugano near the Italian border.
-
B.
Gargnano
Gargnano is a small town on the western shore of Lake Garda in northern Italy, known for its scenic lakeside setting and historic villas.
-
C.
Valdaora
Valdaora is a picturesque alpine municipality in South Tyrol, northern Italy, known for its mountain scenery and proximity to the Dolomites.
-
D.
Pegognaga
Pegognaga is a small Italian municipality in the Lombardy region, known for its agricultural landscape and traditional rural character.
-
E.
Valsassina
Valsassina is an Alpine valley in the Lombardy region of northern Italy, known for its scenic landscapes, traditional villages, and dairy production.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837634248190a99cc454ad1e99e0 |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb8b1b2c8190949943b20f2f8574 |
completed | May 10, 2026, 2:20 a.m. |
Created at: April 10, 2026, 4:57 a.m.