Triple
T4112439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veneti |
E90206
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Venetia |
E40281
|
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: Venetia | Statement: [Veneti, region, Venetia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Venetia Context triple: [Veneti, region, Venetia]
-
A.
Lombardy–Venetia
Lombardy–Venetia was a 19th-century crown land of the Austrian Empire in northern Italy, encompassing the regions of Lombardy and Venetia until their unification with the Kingdom of Italy.
-
B.
Senigallia
Senigallia is a historic coastal town in Italy’s Marche region, known for its Adriatic seaside resort, Renaissance heritage, and well-preserved old town.
-
C.
Triveneto
Triveneto is a historical-geographical region in northeastern Italy that traditionally comprises Veneto, Trentino-Alto Adige/Südtirol, and Friuli Venezia Giulia.
-
D.
Veneto
chosen
Veneto is a region in northeastern Italy known for its historic cities like Venice and Verona, rich cultural heritage, and diverse landscapes ranging from the Adriatic coast to the Dolomite mountains.
-
E.
Emilia-Romagna
Emilia-Romagna is a region in northern Italy known for its rich culinary traditions, historic cities, and strong industrial and agricultural economy.
- 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_69aed95c080881908125e30c5dcdc6f8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af01decd808190b4e5a5f76b090b0a |
completed | March 9, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6133e0b188190b459e1293d5cc2dc |
completed | March 15, 2026, 2:02 a.m. |
Created at: March 9, 2026, 3:41 p.m.