Triple

T35315890
Position Surface form Disambiguated ID Type / Status
Subject Miriwoong language E1019904 entity
Predicate hasDialect P4251 FINISHED
Object Gajirrabeng language
Gajirrabeng is an endangered Aboriginal Australian language of the East Kimberley region, closely related to and sometimes considered a dialect of Miriwoong.
E2134544 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: Gajirrabeng language | Statement: [Miriwoong language, hasDialect, Gajirrabeng language]
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: Gajirrabeng language
Triple: [Miriwoong language, hasDialect, Gajirrabeng language]
Generated description
Gajirrabeng is an endangered Aboriginal Australian language of the East Kimberley region, closely related to and sometimes considered a dialect of Miriwoong.

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_69f76de9d45c81908a2ed0956b448b65 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f790918e2481908851ef7fa47f9d19 completed May 3, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3819f573fc81909835696ae8a6a339 completed June 21, 2026, 5:05 p.m.
NEDg Description generation batch_6a381a89da088190b3b7e52b0531b692 completed June 21, 2026, 5:08 p.m.
NED2 Entity disambiguation (via description) batch_6a381b2726a88190adf96dcab25f5435 completed June 21, 2026, 5:11 p.m.
Created at: May 3, 2026, 4:03 p.m.