Triple

T28075332
Position Surface form Disambiguated ID Type / Status
Subject Mittweida district E709524 entity
Predicate borderedBy P224 FINISHED
Object Chemnitzer Land district
Chemnitzer Land district was a former administrative district in the Free State of Saxony, Germany, located around the city of Chemnitz before being merged into larger districts during regional reforms.
E945811 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: Chemnitzer Land district | Statement: [Mittweida district, borderedBy, Chemnitzer Land district]
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: Chemnitzer Land district
Triple: [Mittweida district, borderedBy, Chemnitzer Land district]
Generated description
Chemnitzer Land district was a former administrative district in the Free State of Saxony, Germany, located around the city of Chemnitz before being merged into larger districts during regional reforms.

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_69ef9b6f8078819098b741274cd1a2ee completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6403f29d481909168f09c19dcbb18 completed May 2, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a162791cf608190875164735639ef96 completed May 26, 2026, 11:06 p.m.
NEDg Description generation batch_6a162892dc4c8190ada51e7571ccb268 completed May 26, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_6a1628f9ec08819083d6da0fa3836c3a completed May 26, 2026, 11:12 p.m.
Created at: April 27, 2026, 8:48 p.m.