Triple
T7749017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Pisa |
E175706
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Pontedera |
E576981
|
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: Pontedera | Statement: [Province of Pisa, containsCity, Pontedera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pontedera Context triple: [Province of Pisa, containsCity, Pontedera]
-
A.
Pontedera
chosen
Pontedera is a town in Tuscany, central Italy, known as an industrial center and the longtime home of the Piaggio (Vespa) manufacturing plant.
-
B.
Viareggio
Viareggio is a coastal city in Tuscany, Italy, renowned for its seaside resorts and famous annual Carnival.
-
C.
Lesignano
Lesignano is a locality or subdivision within the municipality of Serravalle in San Marino.
-
D.
Sarzana
Sarzana is a historic town in the Liguria region of northwestern Italy, known for its medieval fortifications and strategic position near the border with Tuscany.
-
E.
Impruneta
Impruneta is a town in the Tuscany region of central Italy, situated in the hills just south of Florence and known for its terracotta production and scenic countryside.
- 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_69c69960b3588190a53aa590d31d9544 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c703affb6c8190adf4723dc1139edf |
completed | March 27, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8e581d4e881908c88d55364a5e014 |
completed | March 29, 2026, 8:40 a.m. |
Created at: March 27, 2026, 4:08 p.m.