Triple

T37413698
Position Surface form Disambiguated ID Type / Status
Subject Zwickau–Schwarzenberg railway E929641 entity
Predicate openedSection P28341 FINISHED
Object Zwickau–Aue
Zwickau–Aue is a railway section in Saxony, Germany, forming part of the regional line that connects the city of Zwickau with the town of Aue through the Ore Mountains area.
E2230030 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: Zwickau–Aue | Statement: [Zwickau–Schwarzenberg railway, openedSection, Zwickau–Aue]
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: Zwickau–Aue
Triple: [Zwickau–Schwarzenberg railway, openedSection, Zwickau–Aue]
Generated description
Zwickau–Aue is a railway section in Saxony, Germany, forming part of the regional line that connects the city of Zwickau with the town of Aue through the Ore Mountains 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_69f76ebde49481908566cd96b37ccc84 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb8d86ca8c8190aa8fe72272f45c29 completed May 6, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a409521acd481908337b47186f59a29 completed June 28, 2026, 3:29 a.m.
NEDg Description generation batch_6a4095bdb4888190a1bcbff88282e74c completed June 28, 2026, 3:32 a.m.
NED2 Entity disambiguation (via description) batch_6a40965dcecc8190804e4b8849a883a3 completed June 28, 2026, 3:34 a.m.
Created at: May 3, 2026, 4:16 p.m.