Triple

T2671815
Position Surface form Disambiguated ID Type / Status
Subject Robert Schuman E55762 entity
Predicate workLocation P7 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: [Robert Schuman, workLocation, Strasbourg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Strasbourg
Context triple: [Robert Schuman, workLocation, 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. Altkirch
    Altkirch is a small historic town in northeastern France that serves as an administrative and cultural center in the Alsace region.
  • 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_69ab49e54de48190be708cd1cf8be073 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd98f98908190b5c6fb38d3d4367a completed March 7, 2026, 7:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69b203287b48819080791588c7f7f5ab completed March 12, 2026, 12:04 a.m.
Created at: March 6, 2026, 9:54 p.m.