Triple

T9907037
Position Surface form Disambiguated ID Type / Status
Subject Lake Annone E185036 entity
Predicate nearbySettlement P350 FINISHED
Object Oggiono E767510 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: Oggiono | Statement: [Lake Annone, nearbySettlement, Oggiono]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oggiono
Context triple: [Lake Annone, nearbySettlement, Oggiono]
  • A. Oggiono chosen
    Oggiono is a small town and municipality in the Lombardy region of northern Italy, known for its scenic lakeside setting and proximity to the Alps.
  • B. Gargnano
    Gargnano is a small town on the western shore of Lake Garda in northern Italy, known for its scenic lakeside setting and historic villas.
  • C. Pandino
    Pandino is a small Italian town in the Lombardy region, known for its historic Visconti castle and agricultural surroundings.
  • D. Cortabbio
    Cortabbio is a small locality or hamlet that forms part of the municipality of Esino Lario in northern Italy.
  • E. Vimercate
    Vimercate is a town in the Lombardy region of northern Italy, located near Milan and known for its historical center and role as a local economic hub.
  • 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_69ca8296165881908ca4750701af1f29 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb50ec61481908f42bd2aa55d9a6e completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2578390888190b60f3962aec37b2d completed April 5, 2026, 12:37 p.m.
Created at: March 30, 2026, 8:41 p.m.