Triple

T7732117
Position Surface form Disambiguated ID Type / Status
Subject Soest E175283 entity
Predicate hasTwinTown P919 FINISHED
Object Sarreguemines E301984 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: Sarreguemines | Statement: [Soest, hasTwinTown, Sarreguemines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarreguemines
Context triple: [Soest, hasTwinTown, Sarreguemines]
  • A. Sarreguemines chosen
    Sarreguemines is a town in northeastern France near the German border, historically known for its ceramics and faience production.
  • B. Sarrebourg
    Sarrebourg is a small historic town in northeastern France known for its cultural heritage and location in the Moselle department of the Grand Est region.
  • C. Comines
    Comines is a town situated along the Lys River in the historic Flanders region on the border between France and Belgium.
  • D. Pétange
    Pétange is a commune in southwestern Luxembourg known for its proximity to the borders with Belgium and France and its role as a local transport and industrial hub.
  • E. Thionville
    Thionville is a town in northeastern France near the Luxembourg border, known historically as a strategic industrial and military center in the Moselle 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70336aafc819099a060950ab8922f completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be3244088190be26dec90db9cfb3 completed March 29, 2026, 5:52 a.m.
Created at: March 27, 2026, 4:06 p.m.