Triple
T14207998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Salto |
E352150
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Fiamignano |
E368553
|
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: Fiamignano | Statement: [Lake Salto, locatedNear, Fiamignano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fiamignano Context triple: [Lake Salto, locatedNear, Fiamignano]
-
A.
Fiamignano
chosen
Fiamignano is a small Italian municipality in the Lazio region, known for its mountainous landscape and traditional rural character.
-
B.
Schignano
Schignano is a small Italian village in the Lombardy region, known for its traditional Alpine setting and historic Carnival celebrations.
-
C.
Fermignano
Fermignano is a small town in Italy’s Marche region, best known as the birthplace of Renaissance architect and painter Donato Bramante.
-
D.
Poggiardo
Poggiardo is a small town in the Apulia region of southern Italy, known for its archaeological sites and traditional Salento culture.
-
E.
Viareggini
Viareggini are the inhabitants of Viareggio, a Tuscan coastal city in Italy renowned for its beaches and famous Carnival.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61f84f288190877116330bd54393 |
completed | April 14, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a2fdd7c8190b2ebf5a18c8039f2 |
completed | May 8, 2026, 5:52 a.m. |
Created at: April 10, 2026, 1:05 a.m.