Triple
T20731657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Villa Medici at Careggi |
E509585
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Florence city center |
—
|
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: Florence city center | Statement: [Villa Medici at Careggi, near, Florence city center]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Florence city center Context triple: [Villa Medici at Careggi, near, Florence city center]
-
A.
Florence
chosen
Florence is a historic Italian city renowned as the cradle of the Renaissance, celebrated for its art, architecture, and cultural influence.
-
B.
Florence
Florence is a small coastal city in western Oregon known for its scenic beaches, sand dunes, and historic Old Town along the Siuslaw River.
-
C.
Florence
Florence is an unincorporated community within Florence Township in New Jersey, known primarily as a residential area along the Delaware River.
-
D.
Florence
Florence is a small town in Fremont County, Colorado, known for its historic downtown and role as a gateway to nearby outdoor attractions.
-
E.
Florence
Florence is a kind, sensible young girl and one of the main human characters in the classic stop-motion children's television series "The Magic Roundabout."
- 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_69e0b4c589c08190834fb5d86d0efa2b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1ed7e8c8190974f2eb31a0a3106 |
completed | April 21, 2026, 12:16 a.m. |
Created at: April 16, 2026, 12:30 p.m.