Triple
T20533253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Vincenzo |
E504122
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Cecina |
—
|
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: Cecina | Statement: [San Vincenzo, locatedNear, Cecina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cecina Context triple: [San Vincenzo, locatedNear, Cecina]
-
A.
Cecina
chosen
Cecina is a coastal town in Tuscany, Italy, known for its beaches, tourism, and proximity to the Tyrrhenian Sea.
-
B.
Arrecina
Arrecina is an ancient Roman family name (nomen) associated with members of the early Imperial aristocracy.
-
C.
Paesana
Paesana is a small Italian municipality in the Piedmont region, known for its Alpine setting and traditional mountain village character.
-
D.
Bardineto
Bardineto is a small municipality in the Liguria region of northwestern Italy, known for its mountainous surroundings and proximity to the Ligurian Alps.
-
E.
Narón
Narón is a municipality in the province of A Coruña in Galicia, northwestern Spain, known for its close ties to the nearby city of Ferrol and its role in the region’s industrial and service economy.
- 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_69e0b4b476648190bc6019622ae54d3c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a06d30508190a13d1a9855b441fb |
completed | April 20, 2026, 9:53 p.m. |
Created at: April 16, 2026, 11:37 a.m.