Triple

T29919818
Position Surface form Disambiguated ID Type / Status
Subject Verwaltungsgemeinschaft Tutzing E759893 entity
Predicate administers P123 FINISHED
Object municipality of Tutzing
The municipality of Tutzing is a lakeside community in Bavaria, Germany, known for its scenic location on Lake Starnberg and its role as a residential and cultural center in the region.
E1891036 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: municipality of Tutzing | Statement: [Verwaltungsgemeinschaft Tutzing, administers, municipality of Tutzing]
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: municipality of Tutzing
Triple: [Verwaltungsgemeinschaft Tutzing, administers, municipality of Tutzing]
Generated description
The municipality of Tutzing is a lakeside community in Bavaria, Germany, known for its scenic location on Lake Starnberg and its role as a residential and cultural center in the region.

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_69f2246189fc8190996b63ee1f9a2374 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6779293c081909bc5673cec80e607 completed May 2, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a271419a8ec819099d4b2ba1e6a399d completed June 8, 2026, 7:12 p.m.
NEDg Description generation batch_6a27169053048190a44f86999eb062ff completed June 8, 2026, 7:22 p.m.
NED2 Entity disambiguation (via description) batch_6a27174286f4819084d41fe4ebde95e8 completed June 8, 2026, 7:25 p.m.
Created at: April 29, 2026, 6:14 p.m.