Triple

T910977
Position Surface form Disambiguated ID Type / Status
Subject Lombardy E19656 entity
Predicate regionalLanguage P237 FINISHED
Object Lombard E75301 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: Lombard | Statement: [Lombardy, regionalLanguage, Lombard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lombard
Context triple: [Lombardy, regionalLanguage, Lombard]
  • A. Lombard chosen
    Lombard is a Gallo-Italic Romance language traditionally spoken in and around Milan and across much of Lombardy in northern Italy.
  • B. Lucca
    Lucca is a historic Tuscan city renowned for its well-preserved Renaissance walls, medieval architecture, and charming old town.
  • C. Emilian-Romagnol
    Emilian-Romagnol is a Romance language variety spoken primarily in Italy’s Emilia-Romagna region, known for its distinct phonology and vocabulary compared to standard Italian.
  • D. Parma
    Parma is a historic city in northern Italy renowned for its rich artistic heritage, architecture, and culinary traditions, including Parmigiano Reggiano cheese and Parma ham.
  • E. Parla
    Parla is a suburban municipality and residential town located in the southern metropolitan area of Madrid, Spain.
  • 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_69a4939f91a08190ba68c2c81eab90fe completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2de5b008190851852331db41324 completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c73d5bdc8190828cdf9f54e33a46 completed March 4, 2026, 5:46 a.m.
Created at: March 1, 2026, 7:39 p.m.