Triple

T37692920
Position Surface form Disambiguated ID Type / Status
Subject Leopoldau extension E938853 entity
Predicate hasStation P35 FINISHED
Object Aderklaaer Straße station
Aderklaaer Straße station is a Vienna U-Bahn station on the northern extension of Line U1 serving the Leopoldau area.
E2240879 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: Aderklaaer Straße station | Statement: [Leopoldau extension, hasStation, Aderklaaer Straße station]
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: Aderklaaer Straße station
Triple: [Leopoldau extension, hasStation, Aderklaaer Straße station]
Generated description
Aderklaaer Straße station is a Vienna U-Bahn station on the northern extension of Line U1 serving the Leopoldau area.

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_69f76eda6ae48190b3111071eeacc038 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbae1db4008190986cafd89f689e52 completed May 6, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40d6709a7c8190ba2c728d5757ee07 completed June 28, 2026, 8:08 a.m.
NEDg Description generation batch_6a40d8dbcffc8190a6ab2c40f7fe367c completed June 28, 2026, 8:18 a.m.
NED2 Entity disambiguation (via description) batch_6a40da853f3481908753901f2fb07847 completed June 28, 2026, 8:25 a.m.
Created at: May 3, 2026, 4:18 p.m.