Triple
T4816519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Secchia |
E107601
|
entity |
| Predicate | flowsNear |
P350
|
FINISHED |
| Object | Sassuolo |
E365653
|
NE FINISHED |
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: Sassuolo | Statement: [Secchia, flowsNear, Sassuolo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sassuolo Context triple: [Secchia, flowsNear, Sassuolo]
-
A.
Sassuolo
chosen
Sassuolo is an Italian town in the Emilia-Romagna region, known for its ceramics industry and football club U.S. Sassuolo Calcio.
-
B.
Reggiana
Reggiana is an Italian football club based in Reggio Emilia, historically known for competing in the country’s professional leagues.
-
C.
Reggina
Reggina is an Italian professional football club from Reggio Calabria, known for its passionate fan base and history of competing in the country's top divisions.
-
D.
Parma Calcio 1913
Parma Calcio 1913 is an Italian professional football club based in Parma, best known for its successful 1990s era featuring stars like Gianluigi Buffon and multiple European trophy wins.
-
E.
Fiorentina
Fiorentina is a prominent professional football club based in Florence, Italy, known for its rich history, passionate fanbase, and distinctive purple kits.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6c947b18819086c3af556bb7591c |
completed | March 20, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be4db5652081909af5ef92df72c221 |
completed | March 21, 2026, 7:50 a.m. |
Created at: March 20, 2026, 1:23 p.m.