Triple
T21291284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francesco Zolla |
E524795
|
entity |
| Predicate | designed |
P184
|
FINISHED |
| Object | Barrage Zola |
—
|
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: Barrage Zola | Statement: [Francesco Zolla, designed, Barrage Zola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barrage Zola Context triple: [Francesco Zolla, designed, Barrage Zola]
-
A.
Barrage Zola
chosen
Barrage Zola is a notable work by Francesco Zolla, recognized within his body of creative output.
-
B.
Zola Predosa
Zola Predosa is a municipality in the Emilia-Romagna region of northern Italy, situated near the city of Bologna and known for its residential areas and local food and wine production.
-
C.
Zola
Zola is a French surname most famously borne by Émile Zola, the influential 19th-century novelist and leading figure of literary naturalism.
-
D.
Zola
Zola is a township neighborhood in Soweto, South Africa, known for its vibrant street culture and significant role in the country’s urban history.
-
E.
Zola
Zola is a 2020 dark comedy-drama film based on a viral Twitter thread, following a Detroit waitress on a chaotic road trip into the world of stripping and crime.
- 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736da28648190ae3f63c6ba1f6d6f |
completed | April 21, 2026, 8:35 a.m. |
Created at: April 16, 2026, 4:04 p.m.