Triple

T9505446
Position Surface form Disambiguated ID Type / Status
Subject Sarthe E229256 entity
Predicate subprefecture P9697 FINISHED
Object Mamers E803258 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: Mamers | Statement: [Sarthe, subprefecture, Mamers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mamers
Context triple: [Sarthe, subprefecture, Mamers]
  • A. Mamers chosen
    Mamers is a small commune and town in the Sarthe department of northwestern France, known for its traditional markets and historic architecture.
  • B. Duderstadt
    Duderstadt is a historic small town in southern Lower Saxony, Germany, known for its well-preserved medieval timber-framed architecture and role as a regional center in the Eichsfeld area.
  • C. Neustadt
    Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
  • D. Neustadt
    Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
  • E. Melle
    Melle is a town in Lower Saxony, Germany, known for its rural character, historical architecture, and role as a regional economic center.
  • 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_69ca847611c48190a28c028644198c75 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9850fe6c8190a5a96cfae12562c6 completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1526d30a481909944110fd6ebd1dd completed April 4, 2026, 6:03 p.m.
Created at: March 30, 2026, 7:57 p.m.