Triple
T19987126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valdelsa |
E493962
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Alta Valdelsa |
—
|
NE NERFINISHED |
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: Alta Valdelsa | Statement: [Valdelsa, contains, Alta Valdelsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alta Valdelsa Context triple: [Valdelsa, contains, Alta Valdelsa]
-
A.
Valdelsa
Valdelsa is a historical valley area in Tuscany, Italy, known for its medieval hill towns, agricultural landscapes, and cultural heritage.
-
B.
Marecchia Valley
Marecchia Valley is a scenic river valley in the Emilia-Romagna region of Italy, known for its rolling hills, historic villages, and views stretching toward the Adriatic coast.
-
C.
Valdarno
Valdarno is a valley region in Tuscany, Italy, shaped by the Arno River and known for its historic towns and characteristic landscapes.
-
D.
Val di Chiana
Val di Chiana is a fertile valley in central Italy, spanning parts of Tuscany and Umbria, known for its agriculture, historic hill towns, and scenic landscapes.
-
E.
Val d'Elsa
chosen
Val d'Elsa is a scenic area of Tuscany in central Italy, known for its medieval hill towns, vineyards, and rolling countryside.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fdd1a5c8190af756632aac38bf4 |
completed | April 20, 2026, 5:18 p.m. |
Created at: April 11, 2026, 3:29 p.m.