Triple

T8975293
Position Surface form Disambiguated ID Type / Status
Subject County of Flanders E214371 entity
Predicate capital P234 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: [County of Flanders, capital, Lille]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lille
Context triple: [County of Flanders, capital, 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. Métropole Européenne de Lille
    Métropole Européenne de Lille is a major French intercommunal metropolitan authority centered on the city of Lille, coordinating urban planning, transport, and development across numerous surrounding municipalities in northern France.
  • C. Lille Europe
    Lille Europe is a major high-speed railway station in Lille, France, serving international Eurostar and TGV services between the UK and continental Europe.
  • D. Lillebonne
    Lillebonne is a historic town in northern France’s Normandy region, known for its Roman archaeological remains and medieval heritage.
  • E. 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.
  • 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_69ca839dbf608190a2f5990477115d29 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6784d1808190899c980f76084ff8 completed April 1, 2026, 12:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc96aa46c81908b95a23fd2b4da57 completed April 3, 2026, 2:06 p.m.
Created at: March 30, 2026, 7:02 p.m.