Triple

T3841998
Position Surface form Disambiguated ID Type / Status
Subject Moselle E93471 entity
Predicate subprefecture P9697 FINISHED
Object Sarrebourg E294134 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: Sarrebourg | Statement: [Moselle, subprefecture, Sarrebourg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarrebourg
Context triple: [Moselle, subprefecture, Sarrebourg]
  • A. Sarrebourg chosen
    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.
  • B. Sarreguemines
    Sarreguemines is a town in northeastern France near the German border, historically known for its ceramics and faience production.
  • C. Obernai
    Obernai is a historic Alsatian town in northeastern France known for its well-preserved medieval architecture, wine production, and picturesque setting along the Alsace Wine Route.
  • D. 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.
  • E. Haguenau
    Haguenau is a historic town in northeastern France’s Alsace region, known for its medieval heritage, cultural traditions, and role as a local 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_69aed96ce578819084ab16e3439976c9 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeebb397ac81908f74a42a0eeb8682 completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c788a088190aa91261b83f21d86 completed March 14, 2026, 8:29 a.m.
Created at: March 9, 2026, 3:18 p.m.