Triple

T23966148
Position Surface form Disambiguated ID Type / Status
Subject Coswig (Anhalt) E604086 entity
Predicate hasRiverLandscape P165 FINISHED
Object Elbe floodplains
The Elbe floodplains are extensive, ecologically rich river meadows and wetlands along the Elbe River, known for their biodiversity and natural flood protection functions.
E1611356 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: Elbe floodplains | Statement: [Coswig (Anhalt), hasRiverLandscape, Elbe floodplains]
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: Elbe floodplains
Triple: [Coswig (Anhalt), hasRiverLandscape, Elbe floodplains]
Generated description
The Elbe floodplains are extensive, ecologically rich river meadows and wetlands along the Elbe River, known for their biodiversity and natural flood protection functions.

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_69e29543019c8190872462e593cc50b4 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d1d7fbf88190820bcfbdc237c2a3 completed April 29, 2026, 9:39 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7e7732e48190a4cb26b788409595 completed May 21, 2026, 9:51 p.m.
NEDg Description generation batch_6a0f7f21e3608190b646947083391923 completed May 21, 2026, 9:54 p.m.
NED2 Entity disambiguation (via description) batch_6a0f7fcc13c4819080a2590a2b964f9c completed May 21, 2026, 9:57 p.m.
Created at: April 17, 2026, 9:24 p.m.