Triple

T30501635
Position Surface form Disambiguated ID Type / Status
Subject Furth an der Triesting E776152 entity
Predicate hasSubdivision P747 FINISHED
Object Klein-Zell
Klein-Zell is a small locality that forms part of the municipality of Furth an der Triesting in Lower Austria.
E1918810 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: Klein-Zell | Statement: [Furth an der Triesting, hasSubdivision, Klein-Zell]
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: Klein-Zell
Triple: [Furth an der Triesting, hasSubdivision, Klein-Zell]
Generated description
Klein-Zell is a small locality that forms part of the municipality of Furth an der Triesting in Lower Austria.

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_69f22498c5d481908aaea89e6fab8280 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f687812a6481908b126c0aacd38936 completed May 2, 2026, 11:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27be692f5c8190af43013bf3bc0e57 completed June 9, 2026, 7:19 a.m.
NEDg Description generation batch_6a27c26553b48190910c4f93c45aa0db completed June 9, 2026, 7:36 a.m.
NED2 Entity disambiguation (via description) batch_6a27c2ca91448190b09d3c0e77ee23e2 completed June 9, 2026, 7:37 a.m.
Created at: April 29, 2026, 8:14 p.m.