Triple

T1264657
Position Surface form Disambiguated ID Type / Status
Subject Edward Sapir E12573 entity
Predicate placeOfBirth P1 FINISHED
Object Lauenburg in Pommern
Lauenburg in Pommern is a historic town in the former Prussian province of Pomerania, now known as Lębork in northern Poland.
 E158892 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: Lauenburg in Pommern | Statement: [Edward Sapir, placeOfBirth, Lauenburg in Pommern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lauenburg in Pommern
Context triple: [Edward Sapir, placeOfBirth, Lauenburg in Pommern]
  • A. Lauenburg
    Lauenburg is a historic town in northern Germany situated on the banks of the Elbe River.
  • B. Uckermark
    Uckermark is a rural historical region in northeastern Germany, known for its lakes, forests, and low population density, located primarily in the state of Brandenburg.
  • C. Schwerin
    Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
  • D. Lüneburg
    Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
  • E. Rostock
    Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
  • 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: Lauenburg in Pommern
Triple: [Edward Sapir, placeOfBirth, Lauenburg in Pommern]
Generated description
Lauenburg in Pommern is a historic town in the former Prussian province of Pomerania, now known as Lębork in northern Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lauenburg in Pommern
Target entity description: Lauenburg in Pommern is a historic town in the former Prussian province of Pomerania, now known as Lębork in northern Poland.
  • A. Lauenburg
    Lauenburg is a historic town in northern Germany situated on the banks of the Elbe River.
  • B. Uckermark
    Uckermark is a rural historical region in northeastern Germany, known for its lakes, forests, and low population density, located primarily in the state of Brandenburg.
  • C. Schwerin
    Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
  • D. Lüneburg
    Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
  • E. Rostock
    Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
  • 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_69a4933352e08190ac617291985e76c0 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4c03573a48190b5851f0a734c2d6f completed March 1, 2026, 10:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd470b044819087e0adfd137ff037 completed March 8, 2026, 1:44 a.m.
NEDg Description generation batch_69acd7aa69d8819084e154ac82a9ff3c completed March 8, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_69acd7fc5410819092a0c83c89a7c397 completed March 8, 2026, 1:59 a.m.
Created at: March 1, 2026, 7:50 p.m.