Triple

T1435820
Position Surface form Disambiguated ID Type / Status
Subject Ahlden E30556 entity
Predicate locatedNear P294 FINISHED
Object Schwarmstedt
Schwarmstedt is a municipality in Lower Saxony, Germany, situated in the Heidekreis district along the River Aller.
E211319 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: Schwarmstedt | Statement: [Ahlden, locatedNear, Schwarmstedt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwarmstedt
Context triple: [Ahlden, locatedNear, Schwarmstedt]
  • A. Lauenburg
    Lauenburg is a historic town in northern Germany situated on the banks of the Elbe River.
  • B. Wismar
    Wismar is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval architecture and UNESCO-listed old town.
  • C. Maienwerder
    Maienwerder is a small island located in the Tegeler See lake in Berlin, Germany, known for its natural setting and limited accessibility.
  • D. Hasselwerder
    Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
  • E. Delmenhorst
    Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
  • 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: Schwarmstedt
Triple: [Ahlden, locatedNear, Schwarmstedt]
Generated description
Schwarmstedt is a municipality in Lower Saxony, Germany, situated in the Heidekreis district along the River Aller.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Schwarmstedt
Target entity description: Schwarmstedt is a municipality in Lower Saxony, Germany, situated in the Heidekreis district along the River Aller.
  • A. Lauenburg
    Lauenburg is a historic town in northern Germany situated on the banks of the Elbe River.
  • B. Wismar
    Wismar is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval architecture and UNESCO-listed old town.
  • C. Maienwerder
    Maienwerder is a small island located in the Tegeler See lake in Berlin, Germany, known for its natural setting and limited accessibility.
  • D. Hasselwerder
    Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
  • E. Delmenhorst
    Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
  • 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_69a498fc69ec8190b61722bd4b67c4d2 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c50250b88190a0fcf3e0cbba0b1a completed March 1, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69adeabbc9588190880996e549b8bd7a completed March 8, 2026, 9:31 p.m.
NEDg Description generation batch_69adeb6e8fe08190a4732d42aa15ee8e completed March 8, 2026, 9:34 p.m.
NED2 Entity disambiguation (via description) batch_69adebea03a08190bd055e3e6460b5f4 completed March 8, 2026, 9:36 p.m.
Created at: March 1, 2026, 8 p.m.