Triple

T2762135
Position Surface form Disambiguated ID Type / Status
Subject Walter Sickert E61244 entity
Predicate livedIn P75 FINISHED
Object Dieppe E71380 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: Dieppe | Statement: [Walter Sickert, livedIn, Dieppe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dieppe
Context triple: [Walter Sickert, livedIn, Dieppe]
  • A. Dieppe chosen
    Dieppe is a historic port city and seaside resort on the English Channel in northern France, known for its pebbled beaches, cliffs, and role in maritime trade and warfare.
  • B. Dieppe
    Dieppe is a rapidly growing city in southeastern New Brunswick, Canada, located next to Moncton and known for its strong Acadian culture and bilingual community.
  • C. Juno Beach
    Juno Beach was one of the primary Allied landing sectors in Normandy where Canadian forces came ashore during the D-Day invasion of World War II.
  • D. Utah Beach
    Utah Beach was one of the five main Allied landing sites in Normandy during the D-Day invasion of World War II, located on the Cotentin Peninsula and primarily assaulted by American forces.
  • E. Saint-Nazaire
    Saint-Nazaire is a major Atlantic port city in western France, known for its shipbuilding industry and strategic location at the mouth of the Loire River.
  • 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_69ab4b7bab6c8190a5c2efef19a8ef34 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd5072548190946f037c38aabb02 completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc04365448190b37e5ed16c16d650 completed March 10, 2026, 6:54 a.m.
Created at: March 6, 2026, 9:57 p.m.