Triple

T13870864
Position Surface form Disambiguated ID Type / Status
Subject Basse-Ham E333444 entity
Predicate department P1467 FINISHED
Object Moselle E93471 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: Moselle | Statement: [Basse-Ham, department, Moselle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moselle
Context triple: [Basse-Ham, department, Moselle]
  • A. Moselle chosen
    Moselle is a department in northeastern France, bordering Germany and Luxembourg, known for its strategic location, industrial history, and mixed French-German cultural heritage.
  • B. Moselle River
    The Moselle River is a major European waterway flowing through France, Luxembourg, and Germany, renowned for its scenic valleys and wine-producing regions.
  • C. Lower Moselle
    Lower Moselle is a renowned wine-growing subregion along the Moselle River in Germany, noted for its steep slate vineyards and high-quality Riesling wines.
  • D. Saar River
    The Saar River is a major river in northeastern France and western Germany that flows through the industrial region of Saarland before joining the Moselle.
  • E. Merzig
    Merzig is a town in the Saarland region of western Germany, near the borders with France and Luxembourg.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de05c638248190bbe5d19f7b88d0f9 completed April 14, 2026, 9:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd323be8d48190b0b289f25de06fb1 completed May 8, 2026, 12:45 a.m.
Created at: April 9, 2026, 10:14 p.m.