Triple

T3917452
Position Surface form Disambiguated ID Type / Status
Subject Murg E88875 entity
Predicate flowsThrough P225 FINISHED
Object Forbach E296447 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: Forbach | Statement: [Murg, flowsThrough, Forbach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Forbach
Context triple: [Murg, flowsThrough, Forbach]
  • A. Forbach chosen
    Forbach is a town in northeastern France near the German border, known historically for its coal mining industry and cross-border cultural ties.
  • B. Guebwiller
    Guebwiller is a commune in northeastern France known for its wine production and location at the foot of the Vosges mountains in the Alsace region.
  • C. Ribeauvillé
    Ribeauvillé is a historic wine-producing town in France’s Alsace region, known for its medieval architecture and location along the Alsace Wine Route.
  • D. 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.
  • E. Furtwangen
    Furtwangen is a small town in Germany’s Black Forest region, historically known for its clockmaking industry and home to the Furtwangen University of Applied Sciences.
  • 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_69aed955229881909e85e73ffab1d343 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed5797508190adaddb84575d9bb3 completed March 9, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55614ffa48190b15a1c2ec20638f2 completed March 14, 2026, 12:35 p.m.
Created at: March 9, 2026, 3:22 p.m.