Triple
T15578511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lodigiano |
E374430
|
entity |
| Predicate | hasLexicalSimilarityWith |
P11829
|
FINISHED |
| Object | Cremonese |
E705257
|
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: [Lodigiano, hasLexicalSimilarityWith, Cremonese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cremonese Context triple: [Lodigiano, hasLexicalSimilarityWith, Cremonese]
-
A.
Cremona
Cremona is a historic city in northern Italy renowned for its tradition of violin making and its well-preserved medieval architecture.
-
B.
US Cremonese
chosen
US Cremonese is an Italian professional football club based in Cremona, Lombardy, known for competing in the country’s top divisions and for its regional rivalries.
-
C.
Bazzini
Bazzini is an Italian surname most notably associated with the 19th-century violinist and composer Antonio Bazzini.
-
D.
Campello
Campello is a commuter rail station in Brockton, Massachusetts, serving passengers on the MBTA's Middleborough/Lakeville Line.
-
E.
Allegri
Allegri is an Italian football manager and former player best known for his successful tenure as head coach of Juventus.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e24064c8190b132c3092877fbfa |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c4b3a8881909d41204a0b243461 |
completed | May 9, 2026, 3:01 p.m. |
Created at: April 10, 2026, 4:11 a.m.