Triple

T31497805
Position Surface form Disambiguated ID Type / Status
Subject African linguistics E803595 entity
Predicate hasOrganization P629 FINISHED
Object West African Linguistic Society
The West African Linguistic Society is a scholarly association dedicated to the study, documentation, and promotion of the languages of West Africa.
E1965315 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: West African Linguistic Society | Statement: [African linguistics, hasOrganization, West African Linguistic Society]
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: West African Linguistic Society
Triple: [African linguistics, hasOrganization, West African Linguistic Society]
Generated description
The West African Linguistic Society is a scholarly association dedicated to the study, documentation, and promotion of the languages of West Africa.

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_69f348cae52081909fa8e5f697523ae3 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a1eac8688190afdf5732cedf086d completed May 3, 2026, 1:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b146c736c8190b4822f4493777995 completed June 11, 2026, 8:02 p.m.
NEDg Description generation batch_6a2b19ba8ce0819089abdaf2129604a8 completed June 11, 2026, 8:25 p.m.
NED2 Entity disambiguation (via description) batch_6a2b1ab07e38819091fa098750a8de34 completed June 11, 2026, 8:29 p.m.
Created at: April 30, 2026, 9:42 p.m.