Triple
T21399040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florence |
E527861
|
entity |
| Predicate | variantForm |
P4680
|
FINISHED |
| Object | Florencia |
—
|
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: Florencia | Statement: [Florence, variantForm, Florencia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Florencia Context triple: [Florence, variantForm, Florencia]
-
A.
Florencia
chosen
Florencia is a city in southern Colombia that serves as a key gateway between the Andean region and the Amazon rainforest.
-
B.
Florencia
Florencia is the birth name of American singer Vikki Carr, a Grammy-winning vocalist known for her pop and Latin music performances.
-
C.
Florencia
Florencia is a street in Mexico City that intersects at the Glorieta del Ángel, a major roundabout surrounding the iconic Angel of Independence monument.
-
D.
Alvear
Alvear is a small town in the San Martín Department of Corrientes Province in northeastern Argentina, known for its riverside setting along the Uruguay River and regional livestock and agricultural activities.
-
E.
Alvear
Alvear is a town in the Rosario Department of Santa Fe Province, Argentina, functioning as part of the greater Rosario metropolitan area.
- 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.