Triple

T29202985
Position Surface form Disambiguated ID Type / Status
Subject Bundesautobahn 81 E740329 entity
Predicate connectsEconomicCenters P4245 FINISHED
Object Stuttgart metropolitan area
The Stuttgart metropolitan area is a major economic and industrial hub in southwestern Germany, centered on the city of Stuttgart and known for its strong automotive, engineering, and high-tech sectors.
E1454491 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: Stuttgart metropolitan area | Statement: [Bundesautobahn 81, connectsEconomicCenters, Stuttgart metropolitan area]
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: Stuttgart metropolitan area
Triple: [Bundesautobahn 81, connectsEconomicCenters, Stuttgart metropolitan area]
Generated description
The Stuttgart metropolitan area is a major economic and industrial hub in southwestern Germany, centered on the city of Stuttgart and known for its strong automotive, engineering, and high-tech sectors.

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_69f07cb974108190b7e86ca489a6ebb6 completed April 28, 2026, 9:24 a.m.
NER Named-entity recognition batch_69f663c7b4f48190b66f966af570e768 completed May 2, 2026, 8:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f0ef937081908aaeff1288ac4e11 completed June 7, 2026, 10:30 p.m.
NEDg Description generation batch_6a25f647773c8190b06ba76b03d21919 completed June 7, 2026, 10:52 p.m.
NED2 Entity disambiguation (via description) batch_6a25fab4e98081908778fc17fc2a2f60 completed June 7, 2026, 11:11 p.m.
Created at: April 28, 2026, 12:07 p.m.