Triple

T1986005
Position Surface form Disambiguated ID Type / Status
Subject Hanseatic League E43142 entity
Predicate hasMember P10 FINISHED
Object Elbing
Elbing is a historic Baltic port city, now known as Elbląg in Poland, that played a notable role in medieval trade as part of the Hanseatic commercial network.
 E226489 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: Elbing | Statement: [Hanseatic League, hasMember, Elbing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Elbing
Context triple: [Hanseatic League, hasMember, Elbing]
  • A. Vitebsk
    Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
  • B. Orsha
    Orsha is a historic city in eastern Belarus known as a regional transport hub and site of several significant battles.
  • C. Lichtenrade
    Lichtenrade is a southern residential locality of Berlin known for its village-like character, green spaces, and proximity to the city’s outskirts.
  • D. Friedland
    Friedland is a town in present-day Pravdinsk, Russia, historically notable as the site of the decisive 1807 Napoleonic battle between French and Russian forces.
  • E. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • 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: Elbing
Triple: [Hanseatic League, hasMember, Elbing]
Generated description
Elbing is a historic Baltic port city, now known as Elbląg in Poland, that played a notable role in medieval trade as part of the Hanseatic commercial network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Elbing
Target entity description: Elbing is a historic Baltic port city, now known as Elbląg in Poland, that played a notable role in medieval trade as part of the Hanseatic commercial network.
  • A. Vitebsk
    Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
  • B. Orsha
    Orsha is a historic city in eastern Belarus known as a regional transport hub and site of several significant battles.
  • C. Lichtenrade
    Lichtenrade is a southern residential locality of Berlin known for its village-like character, green spaces, and proximity to the city’s outskirts.
  • D. Friedland
    Friedland is a town in present-day Pravdinsk, Russia, historically notable as the site of the decisive 1807 Napoleonic battle between French and Russian forces.
  • E. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • 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_69a88713ddc88190a969715658ebe7a8 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8232d788190938f261fd4b2f2fd completed March 7, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0ad53ccc8190b0e0f44cfddfe9a4 completed March 8, 2026, 11:48 p.m.
NEDg Description generation batch_69ae0b49abfc81908876ea54c7b7dcc2 completed March 8, 2026, 11:50 p.m.
NED2 Entity disambiguation (via description) batch_69ae0d1bb5c881908c27bdd359e78773 completed March 8, 2026, 11:58 p.m.
Created at: March 4, 2026, 7:37 p.m.