Triple
T21291267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francesco Zolla |
E524795
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Barrage Zola
Barrage Zola is a notable work by Francesco Zolla, recognized within his body of creative output.
|
E1476580
|
NE FINISHED |
How this triple was built (4 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, notableWork, Barrage Zola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barrage Zola Context triple: [Francesco Zolla, notableWork, Barrage Zola]
-
A.
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.
-
B.
Zola
Zola is a French surname most famously borne by Émile Zola, the influential 19th-century novelist and leading figure of literary naturalism.
-
C.
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.
-
D.
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.
-
E.
Zabivaka
Zabivaka is the wolf character that served as the official mascot for major international football tournaments hosted by Russia, including the 2018 FIFA World Cup.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Barrage Zola Triple: [Francesco Zolla, notableWork, Barrage Zola]
Generated description
Barrage Zola is a notable work by Francesco Zolla, recognized within his body of creative output.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Barrage Zola Target entity description: Barrage Zola is a notable work by Francesco Zolla, recognized within his body of creative output.
-
A.
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.
-
B.
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.
-
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 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.
-
E.
Zabivaka
Zabivaka is the wolf character that served as the official mascot for major international football tournaments hosted by Russia, including the 2018 FIFA World Cup.
- F. None of above. chosen
Provenance (5 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. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09980e17f0819087ae4fd3712fb584 |
completed | May 17, 2026, 10:27 a.m. |
| NEDg | Description generation | batch_6a0998d6b37881908a1b09afc1f67746 |
completed | May 17, 2026, 10:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0999884e0481909b7ea54cd7ef87b5 |
completed | May 17, 2026, 10:33 a.m. |
Created at: April 16, 2026, 4:04 p.m.