Triple

T3928734
Position Surface form Disambiguated ID Type / Status
Subject Palmengarten E93340 entity
Predicate locatedOnStreet P959 FINISHED
Object Siesmayerstraße
Siesmayerstraße is a street in Frankfurt am Main, Germany, known for bordering the historic Palmengarten botanical garden.
 E442733 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: Siesmayerstraße | Statement: [Palmengarten, locatedOnStreet, Siesmayerstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Siesmayerstraße
Context triple: [Palmengarten, locatedOnStreet, Siesmayerstraße]
  • A. Vorbergstraße
    Vorbergstraße is a residential street located in the Akazienkiez neighborhood of Berlin’s Schöneberg district, known for its quiet, tree-lined character near the area’s lively cafés and shops.
  • B. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • C. Müllerstraße
    Müllerstraße is a major thoroughfare in Berlin’s Wedding district, known for its dense urban character, shops, and public transport connections.
  • D. Schwartzkopffstraße
    Schwartzkopffstraße is a Berlin U-Bahn station on the U6 line located in the central district of the city.
  • E. Braubachstraße
    Braubachstraße is a historic street in Frankfurt’s Altstadt known for its traditional architecture, shops, and proximity to key cultural and tourist sites.
  • 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: Siesmayerstraße
Triple: [Palmengarten, locatedOnStreet, Siesmayerstraße]
Generated description
Siesmayerstraße is a street in Frankfurt am Main, Germany, known for bordering the historic Palmengarten botanical garden.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Siesmayerstraße
Target entity description: Siesmayerstraße is a street in Frankfurt am Main, Germany, known for bordering the historic Palmengarten botanical garden.
  • A. Vorbergstraße
    Vorbergstraße is a residential street located in the Akazienkiez neighborhood of Berlin’s Schöneberg district, known for its quiet, tree-lined character near the area’s lively cafés and shops.
  • B. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • C. Müllerstraße
    Müllerstraße is a major thoroughfare in Berlin’s Wedding district, known for its dense urban character, shops, and public transport connections.
  • D. Schwartzkopffstraße
    Schwartzkopffstraße is a Berlin U-Bahn station on the U6 line located in the central district of the city.
  • E. Braubachstraße
    Braubachstraße is a historic street in Frankfurt’s Altstadt known for its traditional architecture, shops, and proximity to key cultural and tourist sites.
  • 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_69aed96bfa1081908f7b30f2c647dee6 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeeda65b708190b24cd715915aec1d completed March 9, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b627a72da881908e1a4965177727eb completed March 15, 2026, 3:29 a.m.
NEDg Description generation batch_69b628fe10908190978dd0361628f54f completed March 15, 2026, 3:35 a.m.
NED2 Entity disambiguation (via description) batch_69b629ab52c881909f7fbef6f77b5bc4 completed March 15, 2026, 3:38 a.m.
Created at: March 9, 2026, 3:23 p.m.