Triple

T7001809
Position Surface form Disambiguated ID Type / Status
Subject River Reuss E162353 entity
Predicate flowsThrough P225 FINISHED
Object Altdorf E535017 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: Altdorf | Statement: [River Reuss, flowsThrough, Altdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Altdorf
Context triple: [River Reuss, flowsThrough, Altdorf]
  • A. Altdorf
    Altdorf is a Swiss town in the canton of Uri, known as a historic transit point through the Alps and its association with the William Tell legend.
  • B. Urdorf
    Urdorf is a municipality in the canton of Zurich in Switzerland, located in the Limmat Valley near the city of Zurich.
  • C. Altdorf (Uri) chosen
    Altdorf (Uri) is a historic town in central Switzerland, known as the capital of the canton of Uri and closely associated with the William Tell legend.
  • D. Altdorf bei Nürnberg
    Altdorf bei Nürnberg is a small historic town in Bavaria, Germany, known for its former university and proximity to the city of Nuremberg.
  • E. Hemfurth
    Hemfurth is a village in central Germany best known for its proximity to the historic Eder Dam and the Edersee reservoir.
  • 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_69c68857ffc08190857dc62cd5253777 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc1115c48190a9363473ae21b6c1 completed March 27, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a310eb08190a0fc1de2814aea08 completed March 28, 2026, 5:42 a.m.
Created at: March 27, 2026, 2:33 p.m.