Triple

T11887975
Position Surface form Disambiguated ID Type / Status
Subject Gare de Tours E282840 entity
Predicate serves P98 FINISHED
Object city of Tours E560431 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: city of Tours | Statement: [Gare de Tours, serves, city of Tours]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: city of Tours
Context triple: [Gare de Tours, serves, city of Tours]
  • A. city of Tours chosen
    The city of Tours is a historic city in central France, known for its medieval old town, role as a gateway to the Loire Valley châteaux, and rich cultural heritage.
  • B. Poitiers
    Poitiers is a historic city in western France known for its Romanesque architecture, medieval heritage, and role as a regional center in the Nouvelle-Aquitaine region.
  • C. Troyes
    Troyes is a historic city in northeastern France, known for its well-preserved medieval old town, half-timbered houses, and Gothic churches.
  • D. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • E. Saintes
    Saintes is a historic town in southwestern France, known for its well-preserved Roman and medieval heritage, including ancient monuments and religious sites.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8d3a2860c8190a21af5fcddbd2f1e completed April 10, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69f417e919548190acbc248879f957ec completed May 1, 2026, 3:03 a.m.
Created at: April 8, 2026, 9:44 p.m.