Triple

T20200101
Position Surface form Disambiguated ID Type / Status
Subject Egg an der Günz E493190 entity
Predicate hasMayor P185 FINISHED
Object Wolfgang Walter
Wolfgang Walter is a German local politician who serves as the mayor of the Bavarian municipality Egg an der Günz.
E2002649 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: Wolfgang Walter | Statement: [Egg an der Günz, hasMayor, Wolfgang Walter]
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: Wolfgang Walter
Triple: [Egg an der Günz, hasMayor, Wolfgang Walter]
Generated description
Wolfgang Walter is a German local politician who serves as the mayor of the Bavarian municipality Egg an der Günz.

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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66d8d01648190b1b3a6e03f0258d8 completed April 20, 2026, 6:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3056d7b7908190bfec44693723db23 completed June 15, 2026, 7:47 p.m.
NEDg Description generation batch_6a31af0dd4b48190be2aa9c952a9aff6 completed June 16, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_6a31bab61f508190a4bfde1478397f6c completed June 16, 2026, 9:05 p.m.
Created at: April 11, 2026, 11:37 p.m.