Triple

T30759447
Position Surface form Disambiguated ID Type / Status
Subject Ikopa River E783188 entity
Predicate hasHydropowerPlant P15311 FINISHED
Object Antelomita hydropower plant
Antelomita hydropower plant is a hydroelectric facility in Madagascar that generates electricity by harnessing the flow of the Ikopa River.
 E1930868 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: Antelomita hydropower plant | Statement: [Ikopa River, hasHydropowerPlant, Antelomita hydropower plant]
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: Antelomita hydropower plant
Triple: [Ikopa River, hasHydropowerPlant, Antelomita hydropower plant]
Generated description
Antelomita hydropower plant is a hydroelectric facility in Madagascar that generates electricity by harnessing the flow of the Ikopa River.

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_69f224b047f48190b4f5efeb7ee97b37 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68f9a8f888190b7b14dc5b0bc86ca completed May 2, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28b092f4708190bc758b6cb8bebbc5 completed June 10, 2026, 12:32 a.m.
NEDg Description generation batch_6a28b23178f08190976709c4f5806660 completed June 10, 2026, 12:39 a.m.
NED2 Entity disambiguation (via description) batch_6a28b2e6bb048190884738834cd67238 completed June 10, 2026, 12:42 a.m.
Created at: April 29, 2026, 8:39 p.m.