Triple
T3368399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picenum |
E70891
|
entity |
| Predicate | modernEquivalentRegion |
P36806
|
FINISHED |
| Object | Marche |
E62209
|
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: Marche | Statement: [Picenum, modernEquivalentRegion, Marche]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marche Context triple: [Picenum, modernEquivalentRegion, Marche]
-
A.
Louletano
Louletano is the Portuguese demonym used to refer to people or things originating from the city of Loulé in the Algarve region.
-
B.
Marche region
chosen
The Marche region is a central-eastern Italian region on the Adriatic coast, known for its historic hill towns, Renaissance art, and role in early 20th-century political events such as the March on Rome.
-
C.
Aosta
Aosta is a historic town in northwestern Italy known as the capital of the Aosta Valley region and for its well-preserved Roman and medieval architecture.
-
D.
Imperia
Imperia is a coastal city in northwestern Italy’s Liguria region, known for its olive oil production, historic port, and seaside tourism.
-
E.
Franca
Franca is a city in the northeastern part of the Brazilian state of São Paulo, known historically for its leather and footwear industry.
- 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb28a813c81909d1c71fe577e6681 |
completed | March 8, 2026, 5:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b334396f588190add5c0c27949650c |
completed | March 12, 2026, 9:46 p.m. |
Created at: March 8, 2026, 3:13 p.m.