Triple

T719746
Position Surface form Disambiguated ID Type / Status
Subject Alexandre Colonna-Walewski E14389 entity
Predicate placeOfDeath P21 FINISHED
Object Strasbourg E12607 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: Strasbourg | Statement: [Alexandre Colonna-Walewski, placeOfDeath, Strasbourg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Strasbourg
Context triple: [Alexandre Colonna-Walewski, placeOfDeath, Strasbourg]
  • A. Strasbourg chosen
    Strasbourg is a major French city on the Rhine known for hosting key European institutions, including the European Parliament and the Council of Europe.
  • B. Mulhouse
    Mulhouse is an industrial city in northeastern France near the Swiss and German borders, known for its textile heritage and major technical museums.
  • C. Besançon
    Besançon is a historic city in eastern France, known for its well-preserved Vauban fortifications, rich cultural heritage, and role as a regional administrative and educational center.
  • D. Metz
    Metz is a historic city in northeastern France known for its Gothic Saint-Stephen Cathedral, Roman and medieval heritage, and role as the capital of the Moselle department in the Grand Est region.
  • E. Grenoble
    Grenoble is a major city in southeastern France, known for its Alpine setting, universities, and research centers.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a58e65e8819098cba7e6a20d8f33 completed March 1, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5e92d6b0819091fad60317eee455 completed March 7, 2026, 5:21 p.m.
Created at: March 1, 2026, 7:37 p.m.