Triple

T21666799
Position Surface form Disambiguated ID Type / Status
Subject Murik language E534741 entity
Predicate spokenBy P2181 FINISHED
Object Murik people
The Murik people are an indigenous community of Papua New Guinea traditionally living in coastal and lagoon areas of the Sepik region, known for their fishing-based livelihood and distinctive cultural practices.
E1990367 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: Murik people | Statement: [Murik language, spokenBy, Murik people]
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: Murik people
Triple: [Murik language, spokenBy, Murik people]
Generated description
The Murik people are an indigenous community of Papua New Guinea traditionally living in coastal and lagoon areas of the Sepik region, known for their fishing-based livelihood and distinctive cultural practices.

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_69e0c46898008190aa618a4af55bd1ee completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef6c0c236881909ffaefea8601b1c2 completed April 27, 2026, 2 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2eddb816248190940e5dafeac15ae2 completed June 14, 2026, 4:58 p.m.
NEDg Description generation batch_6a2ede66f14c8190886168756794a63e completed June 14, 2026, 5:01 p.m.
NED2 Entity disambiguation (via description) batch_6a2edfcbf05481908b10310ec4536277 completed June 14, 2026, 5:07 p.m.
Created at: April 16, 2026, 6:37 p.m.