Triple

T24912575
Position Surface form Disambiguated ID Type / Status
Subject Riedberg Campus E623886 entity
Predicate region P40 FINISHED
Object Frankfurt-Riedberg district
The Frankfurt-Riedberg district is a modern residential and research area in northern Frankfurt am Main, known especially for hosting major facilities of Goethe University.
E1655897 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: Frankfurt-Riedberg district | Statement: [Riedberg Campus, region, Frankfurt-Riedberg 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: Frankfurt-Riedberg district
Triple: [Riedberg Campus, region, Frankfurt-Riedberg district]
Generated description
The Frankfurt-Riedberg district is a modern residential and research area in northern Frankfurt am Main, known especially for hosting major facilities of Goethe University.

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_69e2fac889c081908e9ff686cb428e5a completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f423899f7c8190b39700fc1b2356c2 completed May 1, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10332c8474819085470c595181feec completed May 22, 2026, 10:42 a.m.
NEDg Description generation batch_6a1033edb6848190b35070d8784af90e completed May 22, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a10348fb55c819087a28d4a7280589c completed May 22, 2026, 10:48 a.m.
Created at: April 18, 2026, 5:28 a.m.