Triple
T9910601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luca Toni |
E185130
|
entity |
| Predicate | club |
P8194
|
FINISHED |
| Object |
Fiorenzuola
Fiorenzuola is an Italian football club based in Fiorenzuola d'Arda, Emilia-Romagna, that has competed primarily in the lower professional divisions.
|
E829601
|
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: Fiorenzuola | Statement: [Luca Toni, club, Fiorenzuola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fiorenzuola Context triple: [Luca Toni, club, Fiorenzuola]
-
A.
Nichelino
Nichelino is a suburban municipality in the Piedmont region of northwestern Italy, located just south of the city of Turin.
-
B.
Reggiana
Reggiana is an Italian football club based in Reggio Emilia, historically known for competing in the country’s professional leagues.
-
C.
Montescudaio
Montescudaio is a small historic town in Tuscany, central Italy, known for its scenic hilltop setting and wine production.
-
D.
Empoli
Empoli is a Tuscan town in central Italy known for its historical center, industrial and agricultural activities, and location along the Arno River west of Florence.
-
E.
Empoli
Empoli is an Italian professional football club based in Empoli, Tuscany, known for competing in Serie A and developing talented players.
- 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: Fiorenzuola Triple: [Luca Toni, club, Fiorenzuola]
Generated description
Fiorenzuola is an Italian football club based in Fiorenzuola d'Arda, Emilia-Romagna, that has competed primarily in the lower professional divisions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fiorenzuola Target entity description: Fiorenzuola is an Italian football club based in Fiorenzuola d'Arda, Emilia-Romagna, that has competed primarily in the lower professional divisions.
-
A.
Nichelino
Nichelino is a suburban municipality in the Piedmont region of northwestern Italy, located just south of the city of Turin.
-
B.
Reggiana
Reggiana is an Italian football club based in Reggio Emilia, historically known for competing in the country’s professional leagues.
-
C.
Montescudaio
Montescudaio is a small historic town in Tuscany, central Italy, known for its scenic hilltop setting and wine production.
-
D.
Empoli
Empoli is a Tuscan town in central Italy known for its historical center, industrial and agricultural activities, and location along the Arno River west of Florence.
-
E.
Empoli
Empoli is an Italian professional football club based in Empoli, Tuscany, known for competing in Serie A and developing talented players.
- 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb512a26881908eb72a21ffb1efef |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20dbfa89881909ea6bbcfcf6fc08f |
completed | April 5, 2026, 7:22 a.m. |
| NEDg | Description generation | batch_69d20ed1f69c819099faa881a9a4368d |
completed | April 5, 2026, 7:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d212e3b864819092b8464f5a5ab696 |
completed | April 5, 2026, 7:44 a.m. |
Created at: March 30, 2026, 8:41 p.m.