Triple

T31371935
Position Surface form Disambiguated ID Type / Status
Subject Schweizer Straße E800185 entity
Predicate partOf P40 FINISHED
Object Frankfurt-Sachsenhausen road network
The Frankfurt-Sachsenhausen road network is the interconnected system of streets and transport routes serving the Sachsenhausen district of Frankfurt am Main, Germany.
E1959575 NE FINISHED

How this triple was built (2 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: Frankfurt-Sachsenhausen road network | Statement: [Schweizer Straße, partOf, Frankfurt-Sachsenhausen road network]
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: Frankfurt-Sachsenhausen road network
Triple: [Schweizer Straße, partOf, Frankfurt-Sachsenhausen road network]
Generated description
The Frankfurt-Sachsenhausen road network is the interconnected system of streets and transport routes serving the Sachsenhausen district of Frankfurt am Main, Germany.

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_69f224e6b7448190ac6bf97ad7364160 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69f8a5d2c81908d4d0d43fc72966f completed May 3, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2a722f8d888190ac9fae844c3d0270 completed June 11, 2026, 8:30 a.m.
NEDg Description generation batch_6a2a7625cb2481909d0b0e710cbecef8 completed June 11, 2026, 8:47 a.m.
NED2 Entity disambiguation (via description) batch_6a2abce7dabc8190b0284b31eade05bb completed June 11, 2026, 1:49 p.m.
Created at: April 29, 2026, 9:18 p.m.