Triple

T2269982
Position Surface form Disambiguated ID Type / Status
Subject John Alcock E50633 entity
Predicate placeOfDeath P21 FINISHED
Object Seine-Maritime E74571 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: Seine-Maritime | Statement: [John Alcock, placeOfDeath, Seine-Maritime]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seine-Maritime
Context triple: [John Alcock, placeOfDeath, Seine-Maritime]
  • A. Seine-Maritime chosen
    Seine-Maritime is a coastal department in the Normandy region of northern France, known for its port city of Le Havre and the historic town of Rouen.
  • B. Ille-et-Vilaine
    Ille-et-Vilaine is a department in northwestern France known for its capital Rennes and its location within the historic region of Brittany.
  • C. Pas-de-Calais
    Pas-de-Calais is a department in northern France, bordering the English Channel and known for its historic ports, World War battlefields, and the Channel Tunnel connection to the United Kingdom.
  • D. Mayenne
    Mayenne is a river in western France that flows through the regions of Normandy and Pays de la Loire before joining other waterways to form the Loire basin.
  • E. Seine-et-Marne
    Seine-et-Marne is a largely rural department in north-central France east of Paris, known for its historic towns, agricultural landscapes, and attractions such as the Château de Fontainebleau and Disneyland Paris.
  • 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_69a88b05910c8190a9a2b1ff230c85f9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1be90708190b8878c393dd2a42d completed March 7, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71d97a108190a26ffd20fac91a7e completed March 9, 2026, 7:08 a.m.
Created at: March 4, 2026, 7:48 p.m.