Triple

T31070364
Position Surface form Disambiguated ID Type / Status
Subject Đa Nhim Reservoir E791798 entity
Predicate locatedNear P294 FINISHED
Object Đa Nhim River
Đa Nhim River is a river in Vietnam’s Central Highlands that feeds the Đa Nhim Reservoir and supports regional hydropower generation and irrigation.
E2062138 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 River | Statement: [Đa Nhim Reservoir, locatedNear, Đa Nhim River]
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 River
Triple: [Đa Nhim Reservoir, locatedNear, Đa Nhim River]
Generated description
Đa Nhim River is a river in Vietnam’s Central Highlands that feeds the Đa Nhim Reservoir and supports regional hydropower generation and irrigation.

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_6a3626f8659c8190880f1474bd96f51b completed June 20, 2026, 5:36 a.m.
NEDg Description generation batch_6a36279033e081909b97ac755ae90116 completed June 20, 2026, 5:39 a.m.
NED2 Entity disambiguation (via description) batch_6a362968a6c08190beb1123ec9f3b337 completed June 20, 2026, 5:47 a.m.
Created at: April 29, 2026, 9:01 p.m.