Triple

T19250450
Position Surface form Disambiguated ID Type / Status
Subject Battle of Marignano E481376 entity
Predicate tookPlaceIn P40 FINISHED
Object Melegnano 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: Melegnano | Statement: [Battle of Marignano, tookPlaceIn, Melegnano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Melegnano
Context triple: [Battle of Marignano, tookPlaceIn, Melegnano]
  • A. Melegnano chosen
    Melegnano is a town in the Lombardy region of northern Italy, historically notable as the site of major Renaissance-era battles including the Battle of Marignano.
  • B. Melzo
    Melzo is a small Italian town and comune in the Lombardy region, situated east of Milan within its metropolitan area.
  • C. Cologno Monzese
    Cologno Monzese is a suburban town in northern Italy known for hosting major television and media studios near Milan.
  • D. Vergiate
    Vergiate is a town in the Lombardy region of northern Italy known for its significant aerospace and helicopter manufacturing facilities.
  • E. Bovisio-Masciago
    Bovisio-Masciago is a small municipality in the Lombardy region of northern Italy, situated in the Brianza area north of Milan.
  • 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_69d8e8cd9d1081908a181d02b88b59b8 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fb3001308190913e24343769be8d completed April 20, 2026, 10:08 a.m.
Created at: April 10, 2026, 1:27 p.m.