Triple

T35694271
Position Surface form Disambiguated ID Type / Status
Subject Para District E1031389 entity
Predicate hasRiver P165 FINISHED
Object Para Creek
Para Creek is a river in Suriname that flows through the Para District, contributing to the region’s drainage and local ecosystems.
E2172344 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: Para Creek | Statement: [Para District, hasRiver, Para Creek]
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: Para Creek
Triple: [Para District, hasRiver, Para Creek]
Generated description
Para Creek is a river in Suriname that flows through the Para District, contributing to the region’s drainage and local ecosystems.

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_69f76e0c73ec819080ab60a9e2f5f1f6 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a07ff0d88190963a3e4ccbb63558 completed May 3, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a390d2b791c8190a30392adb5fd3335 completed June 22, 2026, 10:23 a.m.
NEDg Description generation batch_6a390e01a0208190b82413f513663239 completed June 22, 2026, 10:27 a.m.
NED2 Entity disambiguation (via description) batch_6a39102d69ac81908d9aefcb7c514717 completed June 22, 2026, 10:36 a.m.
Created at: May 3, 2026, 4:05 p.m.