Triple

T27424021
Position Surface form Disambiguated ID Type / Status
Subject Bijagó people E690427 entity
Predicate mainIsland P756 FINISHED
Object Bolama Island
Bolama Island is a historically significant island in Guinea-Bissau’s Bijagós Archipelago, known for its former role as the country’s capital and its rich coastal and cultural heritage.
E2297080 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: Bolama Island | Statement: [Bijagó people, mainIsland, Bolama Island]
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: Bolama Island
Triple: [Bijagó people, mainIsland, Bolama Island]
Generated description
Bolama Island is a historically significant island in Guinea-Bissau’s Bijagós Archipelago, known for its former role as the country’s capital and its rich coastal and cultural heritage.

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_69ef52003fb48190b0f1295246182a86 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62d1f4e8481908387bb7c6956460e completed May 2, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a8301e903d081909b34608be2521c05 completed Aug. 17, 2026, 12:43 p.m.
NEDg Description generation batch_6a8304109a1c8190bd33d939b7052f60 completed Aug. 17, 2026, 12:52 p.m.
NED2 Entity disambiguation (via description) batch_6a830476329c81908fe176f2ca887ec2 completed Aug. 17, 2026, 12:54 p.m.
Created at: April 27, 2026, 12:40 p.m.