Triple

T1424248
Position Surface form Disambiguated ID Type / Status
Subject Ahlden Castle E30292 entity
Predicate nearbySettlement P350 FINISHED
Object Hodenhagen
Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
 E175421 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: Hodenhagen | Statement: [Ahlden Castle, nearbySettlement, Hodenhagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hodenhagen
Context triple: [Ahlden Castle, nearbySettlement, Hodenhagen]
  • A. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • B. Gudhjem
    Gudhjem is a picturesque coastal village on the Danish island of Bornholm, known for its steep streets, red-roofed houses, and harbor overlooking the Baltic Sea.
  • C. Hasselwerder
    Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
  • D. Hassel
    Hassel is a Norwegian surname most notably borne by Nobel Prize–winning chemist Odd Hassel.
  • E. Nyhausen
    Nyhausen is a locality in Germany historically noted as the birthplace of the Swedish nobleman and soldier Philip Christoph von Königsmarck.
  • 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: Hodenhagen
Triple: [Ahlden Castle, nearbySettlement, Hodenhagen]
Generated description
Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hodenhagen
Target entity description: Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
  • A. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • B. Gudhjem
    Gudhjem is a picturesque coastal village on the Danish island of Bornholm, known for its steep streets, red-roofed houses, and harbor overlooking the Baltic Sea.
  • C. Hasselwerder
    Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
  • D. Hassel
    Hassel is a Norwegian surname most notably borne by Nobel Prize–winning chemist Odd Hassel.
  • E. Nyhausen
    Nyhausen is a locality in Germany historically noted as the birthplace of the Swedish nobleman and soldier Philip Christoph von Königsmarck.
  • 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_69a498fb823c8190a67ce4c4837e641a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c4bc145c8190a2d7a1d755d18251 completed March 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad30877a348190a99dbeaf45cd0335 completed March 8, 2026, 8:17 a.m.
NEDg Description generation batch_69ad312e77ac8190b931a42317f2cefa completed March 8, 2026, 8:19 a.m.
NED2 Entity disambiguation (via description) batch_69ad3184853c8190953b288693ce6ea4 completed March 8, 2026, 8:21 a.m.
Created at: March 1, 2026, 8 p.m.