Triple
T14960043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Rinascente |
E373037
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object | Monza |
E107899
|
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: Monza | Statement: [La Rinascente, operatesIn, Monza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monza Context triple: [La Rinascente, operatesIn, Monza]
-
A.
Monza
chosen
Monza is a historic city in northern Italy renowned for its royal villa and the Autodromo Nazionale Monza Formula One racing circuit.
-
B.
Mugello
Mugello is a historic rural region in northern Tuscany, Italy, known for its rolling hills, medieval villages, and cultural heritage.
-
C.
Imola
Imola is a historic city in Italy’s Emilia-Romagna region, best known for its Formula One racing circuit, the Autodromo Enzo e Dino Ferrari.
-
D.
Monza urban area
The Monza urban area is the principal metropolitan zone centered on the city of Monza in northern Italy, known for its dense population, economic activity, and proximity to Milan.
-
E.
Cologno Monzese
Cologno Monzese is a suburban town in northern Italy known for hosting major television and media studios near Milan.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cd85bc81909040b7ff78f62554 |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7ea1d78c81909b877fda05ef9231 |
completed | May 9, 2026, 12:24 a.m. |
Created at: April 10, 2026, 2:40 a.m.