Triple
T12774486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twilight in Italy |
E305331
|
entity |
| Predicate | settingLocation |
P40
|
FINISHED |
| Object | Lake Garda |
E102402
|
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: Lake Garda | Statement: [Twilight in Italy, settingLocation, Lake Garda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Garda Context triple: [Twilight in Italy, settingLocation, Lake Garda]
-
A.
Lake Garda
chosen
Lake Garda is Italy’s largest lake, renowned for its picturesque alpine scenery, mild climate, and popular resort towns.
-
B.
Isola del Garda
Isola del Garda is a picturesque private island on Italy’s Lake Garda, known for its historic Venetian-style villa, lush gardens, and scenic lakeside setting.
-
C.
Lake Iseo
Lake Iseo is a picturesque glacial lake in northern Italy, known for its tranquil scenery, surrounding mountains, and the island of Monte Isola at its center.
-
D.
Lake Gardno
Lake Gardno is a coastal lake in northern Poland known for its location within the Słowiński National Park and its proximity to the Baltic Sea.
-
E.
Lake Varese
Lake Varese is a glacial lake in northern Italy known for its scenic surroundings, birdlife, and rowing activities.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df6b3c88190b0bbe70de8ddcbf3 |
completed | April 10, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684fee60c81909245d4d70c9338c0 |
completed | May 2, 2026, 11:13 p.m. |
Created at: April 9, 2026, 5:29 p.m.