Triple

T17120499
Position Surface form Disambiguated ID Type / Status
Subject Irchel E415450 entity
Predicate hasNearbyArea P4647 FINISHED
Object Schwamendingen
Schwamendingen is a district in the northern part of Zurich, Switzerland, known for its residential neighborhoods and proximity to green recreational areas.
E1250605 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: Schwamendingen | Statement: [Irchel, hasNearbyArea, Schwamendingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwamendingen
Context triple: [Irchel, hasNearbyArea, Schwamendingen]
  • A. Schwansen
    Schwansen is a rural peninsula in northern Germany situated between the Schlei inlet and the Eckernförde Bay in the state of Schleswig-Holstein.
  • B. Gailingen
    Gailingen is a village in the German municipality of Gailingen am Hochrhein in the state of Baden-Württemberg, near the Swiss border along the High Rhine.
  • C. Heerbrugg
    Heerbrugg is a village in the canton of St. Gallen in northeastern Switzerland, known as a regional transport hub and industrial center, particularly for precision optics and surveying technology.
  • D. Schippenbeil
    Schippenbeil is the former German name for the town now known as Sępopol in northeastern Poland.
  • E. Benningen
    Benningen is a municipality in the Unterallgäu district of Bavaria in southern Germany.
  • 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: Schwamendingen
Triple: [Irchel, hasNearbyArea, Schwamendingen]
Generated description
Schwamendingen is a district in the northern part of Zurich, Switzerland, known for its residential neighborhoods and proximity to green recreational areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Schwamendingen
Target entity description: Schwamendingen is a district in the northern part of Zurich, Switzerland, known for its residential neighborhoods and proximity to green recreational areas.
  • A. Schwansen
    Schwansen is a rural peninsula in northern Germany situated between the Schlei inlet and the Eckernförde Bay in the state of Schleswig-Holstein.
  • B. Gailingen
    Gailingen is a village in the German municipality of Gailingen am Hochrhein in the state of Baden-Württemberg, near the Swiss border along the High Rhine.
  • C. Heerbrugg
    Heerbrugg is a village in the canton of St. Gallen in northeastern Switzerland, known as a regional transport hub and industrial center, particularly for precision optics and surveying technology.
  • D. Schippenbeil
    Schippenbeil is the former German name for the town now known as Sępopol in northeastern Poland.
  • E. Benningen
    Benningen is a municipality in the Unterallgäu district of Bavaria in southern Germany.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3e8092b548190b45c1695be47edc2 completed April 18, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a1062fc8190b1c4e97f42cf3faa completed May 11, 2026, 2:08 a.m.
NEDg Description generation batch_6a013ae388548190b09d2c81e1ab0d02 completed May 11, 2026, 2:11 a.m.
NED2 Entity disambiguation (via description) batch_6a013b4df74c81908b3b99e276531e13 completed May 11, 2026, 2:13 a.m.
Created at: April 10, 2026, 5:36 a.m.