Triple

T4357802
Position Surface form Disambiguated ID Type / Status
Subject Hirzel E98591 entity
Predicate hasRoad P959 FINISHED
Object Hirzelstrasse
Hirzelstrasse is a local road in the Swiss village of Hirzel, serving as one of its main thoroughfares.
 E445581 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: Hirzelstrasse | Statement: [Hirzel, hasRoad, Hirzelstrasse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hirzelstrasse
Context triple: [Hirzel, hasRoad, Hirzelstrasse]
  • A. Mühlenstrasse
    Mühlenstrasse is a street in Berlin, Germany, best known for running alongside the East Side Gallery, the longest remaining section of the Berlin Wall.
  • B. Kaufingerstraße
    Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
  • C. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • D. Braubachstraße
    Braubachstraße is a historic street in Frankfurt’s Altstadt known for its traditional architecture, shops, and proximity to key cultural and tourist sites.
  • E. Herbertstraße
    Herbertstraße is a short, gated street in Hamburg’s St. Pauli district known as one of Germany’s most famous red-light prostitution streets.
  • 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: Hirzelstrasse
Triple: [Hirzel, hasRoad, Hirzelstrasse]
Generated description
Hirzelstrasse is a local road in the Swiss village of Hirzel, serving as one of its main thoroughfares.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hirzelstrasse
Target entity description: Hirzelstrasse is a local road in the Swiss village of Hirzel, serving as one of its main thoroughfares.
  • A. Mühlenstrasse
    Mühlenstrasse is a street in Berlin, Germany, best known for running alongside the East Side Gallery, the longest remaining section of the Berlin Wall.
  • B. Kaufingerstraße
    Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
  • C. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • D. Braubachstraße
    Braubachstraße is a historic street in Frankfurt’s Altstadt known for its traditional architecture, shops, and proximity to key cultural and tourist sites.
  • E. Herbertstraße
    Herbertstraße is a short, gated street in Hamburg’s St. Pauli district known as one of Germany’s most famous red-light prostitution streets.
  • 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_69b3454c772081908e20173e379e8ebe completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351c7fa1881908bdc844a7142eb65 completed March 12, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69bb60f8a35481909fffa4af531400eb completed March 19, 2026, 2:35 a.m.
NEDg Description generation batch_69bb69473a608190ab7cc20714e6214f completed March 19, 2026, 3:11 a.m.
NED2 Entity disambiguation (via description) batch_69bb69baaa148190aa005e5bf45b9cd5 completed March 19, 2026, 3:12 a.m.
Created at: March 12, 2026, 11:16 p.m.