Triple

T15612827
Position Surface form Disambiguated ID Type / Status
Subject arrondissement of Sarreguemines E375339 entity
Predicate hasUrbanCenter P2106 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: [arrondissement of Sarreguemines, hasUrbanCenter, Sarreguemines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarreguemines
Context triple: [arrondissement of Sarreguemines, hasUrbanCenter, 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. Berg-sur-Moselle
    Berg-sur-Moselle is a small French commune in the Moselle department of northeastern France, near the border with Luxembourg.
  • D. Comines
    Comines is a town situated along the Lys River in the historic Flanders region on the border between France and Belgium.
  • E. 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.
  • 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e8148a0819087d6d69cc84487ca completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff908b1d6c819086441305b55f81fb completed May 9, 2026, 7:52 p.m.
Created at: April 10, 2026, 4:13 a.m.