Triple

T1276053
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan France E27215 entity
Predicate contains P35 FINISHED
Object Lille E18284 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: Lille | Statement: [Metropolitan France, contains, Lille]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lille
Context triple: [Metropolitan France, contains, Lille]
  • A. Lille chosen
    Lille is a historic industrial and cultural hub in northern France, known for its Flemish-influenced architecture, large student population, and role as a major European transport crossroads.
  • B. Valenciennes
    Valenciennes is a historic industrial city in northern France near the Belgian border, known for its former coal and steel industries and its rich artistic and architectural heritage.
  • C. Villeneuve d’Ascq
    Villeneuve d’Ascq is a suburban city in northern France near Lille, known for its universities, technology parks, and modernist urban planning.
  • D. Lyon
    Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
  • E. Strasbourg
    Strasbourg is a major French city on the Rhine known for hosting key European institutions, including the European Parliament and the Council of Europe.
  • 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_69a496d3710c8190955dee8bc0dacb50 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c08ef32c8190a493c8215946e5dd completed March 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad014954b08190a787d7e03e503d8d completed March 8, 2026, 4:55 a.m.
Created at: March 1, 2026, 7:50 p.m.