Triple
T8572847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gigi Simoni |
E202969
|
entity |
| Predicate | managedClub |
P3239
|
FINISHED |
| Object | Cremonese |
E126825
|
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: Cremonese | Statement: [Gigi Simoni, managedClub, Cremonese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cremonese Context triple: [Gigi Simoni, managedClub, Cremonese]
-
A.
Cremona
chosen
Cremona is a historic city in northern Italy renowned for its tradition of violin making and its well-preserved medieval architecture.
-
B.
Collevecchio
Collevecchio is a small historic town in the Lazio region of central Italy, known for its hilltop setting and traditional rural character.
-
C.
Montescudaio
Montescudaio is a small historic town in Tuscany, central Italy, known for its scenic hilltop setting and wine production.
-
D.
Nichelino
Nichelino is a suburban municipality in the Piedmont region of northwestern Italy, located just south of the city of Turin.
-
E.
Feltrino
Feltrino is a locality in the Province of Belluno in Italy, situated within the mountainous Veneto region of the northeastern Italian Alps.
- 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea43843c8190ac2224d427bb7a75 |
completed | March 31, 2026, 3:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce898cf8648190b52758b6ecf2959b |
completed | April 2, 2026, 3:21 p.m. |
Created at: March 30, 2026, 6:21 p.m.