Triple

T32577614
Position Surface form Disambiguated ID Type / Status
Subject Hohenzollerndamm E832688 entity
Predicate hasJunctionWith P1018 FINISHED
Object Konstanzer Straße
Konstanzer Straße is a street in Berlin, Germany, located in the Charlottenburg-Wilmersdorf district and connected to major thoroughfares such as Hohenzollerndamm.
E2159283 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: Konstanzer Straße | Statement: [Hohenzollerndamm, hasJunctionWith, Konstanzer Straße]
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: Konstanzer Straße
Triple: [Hohenzollerndamm, hasJunctionWith, Konstanzer Straße]
Generated description
Konstanzer Straße is a street in Berlin, Germany, located in the Charlottenburg-Wilmersdorf district and connected to major thoroughfares such as Hohenzollerndamm.

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_69f349289adc81909f4374a58ec35a39 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c640c85481909bdd34f36234a438 completed May 3, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a38a4c6f43c8190a1bc1fbd0c912f78 completed June 22, 2026, 2:58 a.m.
NEDg Description generation batch_6a38a57d5e2c81908a749015ac6fcd7f completed June 22, 2026, 3:01 a.m.
NED2 Entity disambiguation (via description) batch_6a38a5fa291c81909955855947ef19d5 completed June 22, 2026, 3:03 a.m.
Created at: May 1, 2026, 1:04 a.m.