Triple

T9859007
Position Surface form Disambiguated ID Type / Status
Subject Coburg district E239658 entity
Predicate contains P35 FINISHED
Object Neustadt bei Coburg E534619 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: Neustadt bei Coburg | Statement: [Coburg district, contains, Neustadt bei Coburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neustadt bei Coburg
Context triple: [Coburg district, contains, Neustadt bei Coburg]
  • A. Neustadt bei Coburg chosen
    Neustadt bei Coburg is a small town in northern Bavaria, Germany, known for its traditional toy-making industry and location near the Thuringian border.
  • B. Neustadt an der Waldnaab
    Neustadt an der Waldnaab is a small town in northeastern Bavaria, Germany, known for its historic center and location along the Waldnaab River.
  • C. Neustadt an der Aisch
    Neustadt an der Aisch is a small town in the Bavarian region of Germany, known for its historic center and location along the Aisch River between Würzburg and Nuremberg.
  • D. Bad Neustadt an der Saale
    Bad Neustadt an der Saale is a small spa town in northern Bavaria, Germany, known for its historic old town and health resorts along the Saale River.
  • E. Neustadt
    Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
  • 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_69ca84e6493081909cf58c8d42ea856b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb39b06b48190ab53ff00ff0513ca completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d380c81c7c81908361d237d79f1ff0 completed April 6, 2026, 9:45 a.m.
Created at: March 30, 2026, 8:35 p.m.