Triple

T16293107
Position Surface form Disambiguated ID Type / Status
Subject Unna district E395574 entity
Predicate containsTown P847 FINISHED
Object Selm E992300 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: Selm | Statement: [Unna district, containsTown, Selm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Selm
Context triple: [Unna district, containsTown, Selm]
  • A. Selm chosen
    Selm is a small town in the German state of North Rhine-Westphalia, located in the Ruhr area.
  • B. Eidsberg
    Eidsberg is a former municipality and rural town area in southeastern Norway, historically part of Østfold county and known for its agricultural landscape and cultural heritage.
  • C. Lonsee
    Lonsee is a small municipality in the Alb-Donau district of Baden-Württemberg, Germany, situated on the Swabian Jura near the city of Ulm.
  • D. Balve
    Balve is a small town in the Märkischer Kreis district of North Rhine-Westphalia, Germany, known for its limestone caves and scenic Sauerland surroundings.
  • E. Garmsar
    Garmsar is a city in Semnan Province of north-central Iran, known as a regional transport hub and gateway between Tehran and eastern parts of the country.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e25e2aee6881909fd28547f135427c completed April 17, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f97895081909f22ded3507afe14 completed May 10, 2026, 6:03 a.m.
Created at: April 10, 2026, 5:05 a.m.