Triple

T24449128
Position Surface form Disambiguated ID Type / Status
Subject Lewis Pass E616482 entity
Predicate riverValley P165 FINISHED
Object Maruia River
The Maruia River is a scenic river in New Zealand’s South Island that flows through rugged forested valleys and geothermal areas before joining the Buller River.
E2098459 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: Maruia River | Statement: [Lewis Pass, riverValley, Maruia 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: Maruia River
Triple: [Lewis Pass, riverValley, Maruia River]
Generated description
The Maruia River is a scenic river in New Zealand’s South Island that flows through rugged forested valleys and geothermal areas before joining the Buller 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_69e2d7edca608190aafefc8877a1b4da completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f298562c6c8190a7374508f7237be2 completed April 29, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37210eedac8190af814ff2a1059ac4 completed June 20, 2026, 11:23 p.m.
NEDg Description generation batch_6a37221583e48190a3dbe0dc7ad27453 completed June 20, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_6a3722b425808190a8453a3e71d14066 completed June 20, 2026, 11:31 p.m.
Created at: April 18, 2026, 2:18 a.m.