Triple
T21399032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florence |
E527861
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Florina |
—
|
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: Florina | Statement: [Florence, relatedName, Florina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Florina Context triple: [Florence, relatedName, Florina]
-
A.
Florina
chosen
Florina is a town in northern Greece known for its mountainous landscape, cold winters, and role as a regional cultural and administrative center.
-
B.
Litochoro
Litochoro is a Greek town situated at the foot of Mount Olympus, known as a popular base for hiking and exploring the surrounding national park.
-
C.
Idomeni
Idomeni is a small Greek village near the border with North Macedonia, known as a key rail and road crossing point and as a major transit site during the European migrant crisis.
-
D.
Arachova
Arachova is a picturesque mountain town in central Greece, known for its traditional stone architecture, ski resort, and proximity to the ancient site of Delphi.
-
E.
Vlahi
Vlahi are an ethnographic group in Istria who identify as Vlachs, a Romance-speaking people historically spread across parts of the Balkans.
- 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_69e0b520ee3c8190abddbee7e37e834c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee62cf3e808190847ad66d2e65f9f2 |
completed | April 26, 2026, 7:09 p.m. |
Created at: April 16, 2026, 5:14 p.m.