Triple

T1088099
Position Surface form Disambiguated ID Type / Status
Subject Bologna E24097 entity
Predicate nickname P55 FINISHED
Object La Grassa
La Grassa is a famous nickname for the Italian city of Bologna, highlighting its rich culinary tradition and renowned food culture.
 E126087 NE FINISHED

How this triple was built (4 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: La Grassa | Statement: [Bologna, nickname, La Grassa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: La Grassa
Context triple: [Bologna, nickname, La Grassa]
  • A. Gavignano
    Gavignano is a small Italian town in the Lazio region, historically notable as the birthplace of Pope Innocent III.
  • B. Pontcharra
    Pontcharra is a small French commune in the Isère department of southeastern France, situated in the Grésivaudan valley between Grenoble and Chambéry.
  • C. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • D. Tartegnin
    Tartegnin is a small wine-producing municipality in the canton of Vaud in western Switzerland, situated above Lake Geneva in the La Côte region.
  • E. Bernardin
    Bernardin is a well-known brand specializing in home canning and preserving supplies, particularly mason jars, lids, and related accessories.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: La Grassa
Triple: [Bologna, nickname, La Grassa]
Generated description
La Grassa is a famous nickname for the Italian city of Bologna, highlighting its rich culinary tradition and renowned food culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: La Grassa
Target entity description: La Grassa is a famous nickname for the Italian city of Bologna, highlighting its rich culinary tradition and renowned food culture.
  • A. Gavignano
    Gavignano is a small Italian town in the Lazio region, historically notable as the birthplace of Pope Innocent III.
  • B. Pontcharra
    Pontcharra is a small French commune in the Isère department of southeastern France, situated in the Grésivaudan valley between Grenoble and Chambéry.
  • C. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • D. Tartegnin
    Tartegnin is a small wine-producing municipality in the canton of Vaud in western Switzerland, situated above Lake Geneva in the La Côte region.
  • E. Bernardin
    Bernardin is a well-known brand specializing in home canning and preserving supplies, particularly mason jars, lids, and related accessories.
  • F. None of above. chosen

Provenance (5 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_69a49404428c819092dcc9632f5f7b8b completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b97d85708190a1630256648aa4a2 completed March 1, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c243cbc81908d6101faad628fc8 completed March 7, 2026, 4:02 p.m.
NEDg Description generation batch_69ac4cae760881909329701561ad2ba6 completed March 7, 2026, 4:05 p.m.
NED2 Entity disambiguation (via description) batch_69ac4d7176808190b74d535d7e1b7c6a completed March 7, 2026, 4:08 p.m.
Created at: March 1, 2026, 7:42 p.m.