Triple

T30063440
Position Surface form Disambiguated ID Type / Status
Subject District of Schwaz E763959 entity
Predicate hasMunicipality P847 FINISHED
Object Bruck am Ziller
Bruck am Ziller is a small municipality in the Tyrolean Alps of western Austria, situated in the Ziller Valley within the administrative area of the Schwaz district.
E1904150 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: Bruck am Ziller | Statement: [District of Schwaz, hasMunicipality, Bruck am Ziller]
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: Bruck am Ziller
Triple: [District of Schwaz, hasMunicipality, Bruck am Ziller]
Generated description
Bruck am Ziller is a small municipality in the Tyrolean Alps of western Austria, situated in the Ziller Valley within the administrative area of the Schwaz district.

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_69f2247221388190a13a22c47094a0ef completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67ca4dc388190a6f3cf48f2fad819 completed May 2, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27582304d88190abaa3805dad3363b completed June 9, 2026, 12:02 a.m.
NEDg Description generation batch_6a275a7d33848190ba11aeb45c7e8b83 completed June 9, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_6a275b11987081908ec648ce1eeceed3 completed June 9, 2026, 12:15 a.m.
Created at: April 29, 2026, 6:58 p.m.