Triple

T31070352
Position Surface form Disambiguated ID Type / Status
Subject Đa Nhim Reservoir E791798 entity
Predicate usedBy P260 FINISHED
Object Đa Nhim Hydropower Plant
Đa Nhim Hydropower Plant is a major hydroelectric power station in Vietnam’s Central Highlands that generates electricity using water from the Đa Nhim River system.
E1951176 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: Đa Nhim Hydropower Plant | Statement: [Đa Nhim Reservoir, usedBy, Đa Nhim 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: Đa Nhim Hydropower Plant
Triple: [Đa Nhim Reservoir, usedBy, Đa Nhim Hydropower Plant]
Generated description
Đa Nhim Hydropower Plant is a major hydroelectric power station in Vietnam’s Central Highlands that generates electricity using water from the Đa Nhim River system.

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_69f224cc0c5c81908404f087bff92997 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f695b566388190a0e6018bf397aa67 completed May 3, 2026, 12:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2958fa98508190987da52f42614a92 completed June 10, 2026, 12:30 p.m.
NEDg Description generation batch_6a295d3fbc848190aaa485d91b2a4bc1 completed June 10, 2026, 12:49 p.m.
NED2 Entity disambiguation (via description) batch_6a295f0717208190a12dd4058b721fb2 completed June 10, 2026, 12:56 p.m.
Created at: April 29, 2026, 9:01 p.m.