Triple

T26906290
Position Surface form Disambiguated ID Type / Status
Subject KMDA E677263 entity
Predicate manages P86 FINISHED
Object De Zegge nature reserve
De Zegge nature reserve is a protected wetland and nature area in Belgium known for its rich biodiversity and conservation of rare plant and animal species.
 E1748826 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: De Zegge nature reserve | Statement: [KMDA, manages, De Zegge nature reserve]
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: De Zegge nature reserve
Triple: [KMDA, manages, De Zegge nature reserve]
Generated description
De Zegge nature reserve is a protected wetland and nature area in Belgium known for its rich biodiversity and conservation of rare plant and animal species.

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_69eee9bcef1c8190be88586bb902bb9b completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61fd623bc819091df736cf3419b99 completed May 2, 2026, 4:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121eac20e48190b21c1cf5de1ad4e2 completed May 23, 2026, 9:39 p.m.
NEDg Description generation batch_6a12227c0b2c8190b50c3c2b8c23f28f completed May 23, 2026, 9:56 p.m.
NED2 Entity disambiguation (via description) batch_6a1222f3a7908190b14251b4c12c5276 completed May 23, 2026, 9:58 p.m.
Created at: April 27, 2026, 5:59 a.m.