Triple

T38125508
Position Surface form Disambiguated ID Type / Status
Subject Andorf E952055 entity
Predicate hasTransportConnection P845 FINISHED
Object B137 Innviertler Straße
B137 Innviertler Straße is a federal highway in Austria that serves as a key regional route through the Innviertel area, connecting several towns and facilitating local and cross-border traffic.
E2256430 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: B137 Innviertler Straße | Statement: [Andorf, hasTransportConnection, B137 Innviertler 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: B137 Innviertler Straße
Triple: [Andorf, hasTransportConnection, B137 Innviertler Straße]
Generated description
B137 Innviertler Straße is a federal highway in Austria that serves as a key regional route through the Innviertel area, connecting several towns and facilitating local and cross-border traffic.

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_69f76f083548819082bd2bbf53c79e8e completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc45e3ed48819083230996ffdd3d5e completed May 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a41682370648190aa8c4475e87590a4 completed June 28, 2026, 6:29 p.m.
NEDg Description generation batch_6a4168bb69648190a6d588ccf599648e completed June 28, 2026, 6:32 p.m.
NED2 Entity disambiguation (via description) batch_6a41694820f8819093ccc0249774cf13 completed June 28, 2026, 6:34 p.m.
Created at: May 3, 2026, 4:21 p.m.