Triple

T31130193
Position Surface form Disambiguated ID Type / Status
Subject Pa'a E793480 entity
Predicate hasNeighborLanguage P16383 FINISHED
Object Ciwogai
Ciwogai is a lesser-known indigenous language of Nigeria, spoken in close geographic and cultural proximity to the Pa'a language.
E1947920 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: Ciwogai | Statement: [Pa'a, hasNeighborLanguage, Ciwogai]
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: Ciwogai
Triple: [Pa'a, hasNeighborLanguage, Ciwogai]
Generated description
Ciwogai is a lesser-known indigenous language of Nigeria, spoken in close geographic and cultural proximity to the Pa'a language.

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_69f224d1701c819094f429798290e361 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6973f7d948190a1e2ff726d61ebb1 completed May 3, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2938c70568819095ac2846e88df13d completed June 10, 2026, 10:13 a.m.
NEDg Description generation batch_6a293d28ee7c81908c2e7530950d0d95 completed June 10, 2026, 10:32 a.m.
NED2 Entity disambiguation (via description) batch_6a293d9c72148190a65a2603f2757efa completed June 10, 2026, 10:34 a.m.
Created at: April 29, 2026, 9:05 p.m.