Triple

T17049898
Position Surface form Disambiguated ID Type / Status
Subject Tauber E413664 entity
Predicate flowsThrough P225 FINISHED
Object Creglingen E1248414 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: Creglingen | Statement: [Tauber, flowsThrough, Creglingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Creglingen
Context triple: [Tauber, flowsThrough, Creglingen]
  • A. Creglingen chosen
    Creglingen is a small historic town in southern Germany’s Tauber Valley, known for its well-preserved medieval architecture and notable religious art.
  • B. Rinklingen
    Rinklingen is a district or locality within the town of Bretten in the state of Baden-Württemberg, Germany.
  • C. Iclingas
    The Iclingas were the early royal dynasty of the Anglo-Saxon kingdom of Mercia, traditionally tracing their lineage back to the legendary figure Icel.
  • D. Hagenborgh
    Hagenborgh is a notable landmark building in the Dutch city of Almelo, recognized for its prominent role in the local urban landscape.
  • E. Sippenaeken
    Sippenaeken is a small village in eastern Belgium, near the Dutch and German borders, known for its rural landscape and historic church.
  • 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_69d886cde3d481908d4d01ba88ba7eb7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3daa1aeac81909e8d97bd708c6b71 completed April 18, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139f17a5481908896c1c6ff326c2f completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:34 a.m.