Triple

T28058811
Position Surface form Disambiguated ID Type / Status
Subject Aspern Airfield E709044 entity
Predicate near P350 FINISHED
Object Aspern junction of A23 and S2 motorways
The Aspern junction of the A23 and S2 motorways is a major road interchange in Vienna’s Aspern district, providing a key connection between the city’s outer ring routes and eastern suburbs.
 E1799052 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: Aspern junction of A23 and S2 motorways | Statement: [Aspern Airfield, near, Aspern junction of A23 and S2 motorways]
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: Aspern junction of A23 and S2 motorways
Triple: [Aspern Airfield, near, Aspern junction of A23 and S2 motorways]
Generated description
The Aspern junction of the A23 and S2 motorways is a major road interchange in Vienna’s Aspern district, providing a key connection between the city’s outer ring routes and eastern suburbs.

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_69ef9b6eb6d88190a3fea236eb0f7bed completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f63fde4030819089d26a7e7c9d713e completed May 2, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b8c59f788190ada1254a87d0506e completed May 26, 2026, 3:14 p.m.
NEDg Description generation batch_6a15ba5218f88190b93cfdf2c120de99 completed May 26, 2026, 3:20 p.m.
NED2 Entity disambiguation (via description) batch_6a15bb27200c8190bf9e7a14821f054a completed May 26, 2026, 3:24 p.m.
Created at: April 27, 2026, 8:38 p.m.