Triple

T26191515
Position Surface form Disambiguated ID Type / Status
Subject Madagascar lowland forests E654975 entity
Predicate borderedBy P224 FINISHED
Object Madagascar mangroves
Madagascar mangroves are coastal wetland ecosystems of salt-tolerant trees and shrubs that fringe Madagascar’s shorelines, providing critical habitat for wildlife and protection against coastal erosion.
E1713372 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: Madagascar mangroves | Statement: [Madagascar lowland forests, borderedBy, Madagascar mangroves]
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: Madagascar mangroves
Triple: [Madagascar lowland forests, borderedBy, Madagascar mangroves]
Generated description
Madagascar mangroves are coastal wetland ecosystems of salt-tolerant trees and shrubs that fringe Madagascar’s shorelines, providing critical habitat for wildlife and protection against coastal erosion.

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_69ee5b469bc081908fe486453fdad810 completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60ca25acc81908bfe2d4ba1107748 completed May 2, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11857a57a08190a55c86f241f5dc12 completed May 23, 2026, 10:46 a.m.
NEDg Description generation batch_6a11861e622c8190a73ab247d696435a completed May 23, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a1186c04c2c8190a5e70c9d9a5cbeb8 completed May 23, 2026, 10:51 a.m.
Created at: April 26, 2026, 8:44 p.m.