Triple

T26295122
Position Surface form Disambiguated ID Type / Status
Subject Sunda Strait islands E661392 entity
Predicate hasNotableIsland P970 FINISHED
Object Sangiang Island
Sangiang Island is a small volcanic island and marine nature reserve in the Sunda Strait of Indonesia, known for its rich coral reefs, diverse marine life, and scenic coastal landscapes.
E2295934 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: Sangiang Island | Statement: [Sunda Strait islands, hasNotableIsland, Sangiang 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: Sangiang Island
Triple: [Sunda Strait islands, hasNotableIsland, Sangiang Island]
Generated description
Sangiang Island is a small volcanic island and marine nature reserve in the Sunda Strait of Indonesia, known for its rich coral reefs, diverse marine life, and scenic coastal landscapes.

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_69ee812cd48c81908054068f545f0526 completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60ead95e08190bff727f2dac46eea completed May 2, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a82115e4f24819083e7f026bcbd3d2a completed Aug. 16, 2026, 7:37 p.m.
NEDg Description generation batch_6a82119ee4148190aa5ef30d17d8e3bb completed Aug. 16, 2026, 7:38 p.m.
NED2 Entity disambiguation (via description) batch_6a8211f24bdc81908ec016184b6a52bb completed Aug. 16, 2026, 7:39 p.m.
Created at: April 26, 2026, 10:11 p.m.