Triple

T16817516
Position Surface form Disambiguated ID Type / Status
Subject Lille-Flandres E408791 entity
Predicate connectsToCity P4245 FINISHED
Object Roubaix E223522 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: Roubaix | Statement: [Lille-Flandres, connectsToCity, Roubaix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roubaix
Context triple: [Lille-Flandres, connectsToCity, Roubaix]
  • A. Roubaix chosen
    Roubaix is a city in northern France known for its textile industry heritage and as the finish of the Paris–Roubaix professional cycling race.
  • B. La Route des Flandres
    La Route des Flandres is a 1960 novel by French writer Claude Simon, noted for its fragmented, stream-of-consciousness portrayal of soldiers’ experiences during World War II and considered a key work of the Nouveau Roman movement.
  • C. Kuurne
    Kuurne is a municipality in the Belgian province of West Flanders, situated near the city of Kortrijk.
  • D. Côte de Beauté
    Côte de Beauté is a scenic stretch of Atlantic coastline in southwestern France, known for its sandy beaches, seaside resorts, and mild climate.
  • E. Balignicourt
    Balignicourt is a small commune in the Aube department of north-central France.
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b2e30cf48190a61936ba0a49df24 completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00b297778c81909a2545c359739151 completed May 10, 2026, 4:30 p.m.
Created at: April 10, 2026, 5:23 a.m.