Triple

T9826859
Position Surface form Disambiguated ID Type / Status
Subject Krems an der Donau E238677 entity
Predicate hasPart P35 FINISHED
Object Angern
Angern is a locality within the Austrian city of Krems an der Donau, situated in the federal state of Lower Austria.
E822984 NE FINISHED

How this triple was built (4 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: Angern | Statement: [Krems an der Donau, hasPart, Angern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Angern
Context triple: [Krems an der Donau, hasPart, Angern]
  • A. Spremberg
    Spremberg is a small town in eastern Germany’s Lusatia region, known for its location along the River Spree and its historic town center.
  • B. Reinsberg
    Reinsberg is a municipality in the German state of Saxony, located within the administrative district of Mittelsachsen.
  • C. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • D. Pellinge
    Pellinge is a small island village in the Pellinge archipelago off the southern coast of Finland, known for its traditional fishing community and scenic Baltic Sea landscapes.
  • E. Zahle
    Zahle is a prominent city in Lebanon’s Beqaa Valley, known for its historic architecture, vineyards, and role as a regional commercial and cultural center.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Angern
Triple: [Krems an der Donau, hasPart, Angern]
Generated description
Angern is a locality within the Austrian city of Krems an der Donau, situated in the federal state of Lower Austria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Angern
Target entity description: Angern is a locality within the Austrian city of Krems an der Donau, situated in the federal state of Lower Austria.
  • A. Spremberg
    Spremberg is a small town in eastern Germany’s Lusatia region, known for its location along the River Spree and its historic town center.
  • B. Reinsberg
    Reinsberg is a municipality in the German state of Saxony, located within the administrative district of Mittelsachsen.
  • C. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • D. Pellinge
    Pellinge is a small island village in the Pellinge archipelago off the southern coast of Finland, known for its traditional fishing community and scenic Baltic Sea landscapes.
  • E. Zahle
    Zahle is a prominent city in Lebanon’s Beqaa Valley, known for its historic architecture, vineyards, and role as a regional commercial and cultural center.
  • F. None of above. chosen

Provenance (5 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb324e7848190b9424a78ca653afe completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc88a86c819088f259a049eec4db completed April 5, 2026, 2:44 a.m.
NEDg Description generation batch_69d1cdba64d08190bf0b83d419c4461b completed April 5, 2026, 2:49 a.m.
NED2 Entity disambiguation (via description) batch_69d1ce526a2c819098b103ad83c19445 completed April 5, 2026, 2:52 a.m.
Created at: March 30, 2026, 8:32 p.m.