Triple

T36663178
Position Surface form Disambiguated ID Type / Status
Subject Central Chadic peoples E905188 entity
Predicate includesEthnicGroup P1898 FINISHED
Object Giziga people
The Giziga people are an ethnic group of the Central Chadic cultural-linguistic sphere, primarily inhabiting northern Cameroon and speaking a Chadic language.
E2210161 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: Giziga people | Statement: [Central Chadic peoples, includesEthnicGroup, Giziga 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: Giziga people
Triple: [Central Chadic peoples, includesEthnicGroup, Giziga people]
Generated description
The Giziga people are an ethnic group of the Central Chadic cultural-linguistic sphere, primarily inhabiting northern Cameroon and speaking a Chadic 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_69f76e6e3b908190970251b30f76ad71 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c77e245c8190b46c46be05e7a30c completed May 3, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e8c1bbe9c81909261e9c288da73c0 completed June 26, 2026, 2:26 p.m.
NEDg Description generation batch_6a3e9bc7edd48190822561cc620b4e6b completed June 26, 2026, 3:33 p.m.
NED2 Entity disambiguation (via description) batch_6a3ea0e383e081909dbc3c557aae2054 completed June 26, 2026, 3:55 p.m.
Created at: May 3, 2026, 4:12 p.m.