Triple

T10018565
Position Surface form Disambiguated ID Type / Status
Subject Aricia E199556 entity
Predicate laterName P65 FINISHED
Object Ariccia E614069 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: Ariccia | Statement: [Aricia, laterName, Ariccia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ariccia
Context triple: [Aricia, laterName, Ariccia]
  • A. Ariccia chosen
    Ariccia is a historic town in the Alban Hills near Rome, known for its Baroque architecture and traditional porchetta.
  • B. Vetralla
    Vetralla is a historic town and comune in the Lazio region of central Italy, known for its medieval architecture and location along the ancient Via Cassia.
  • C. Isernia
    Isernia is a historic town and provincial capital in the Molise region of southern-central Italy, known for its ancient Samnite and Roman roots.
  • D. Pisae
    Pisae is the ancient Roman name for the city of Pisa in Tuscany, Italy, historically significant as a coastal settlement and later a prominent maritime republic.
  • E. Cascia
    Cascia is a historic hill town and pilgrimage site in the Umbria region of central Italy, best known for its association with Saint Rita of Cascia.
  • 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_69ca8315a1a08190ab310f25620f362b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd4de1588190a89ed575cff0b8c9 completed April 2, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e559a1608190903e9b2dff12bb00 completed April 5, 2026, 10:42 p.m.
Created at: March 30, 2026, 8:53 p.m.