Triple

T27153155
Position Surface form Disambiguated ID Type / Status
Subject Sawusea E682444 entity
Predicate hasIsland P970 FINISHED
Object Semau Island
Semau Island is a small Indonesian island located just off the western coast of Timor in East Nusa Tenggara Province, known for its traditional villages, dry landscapes, and surrounding coral reefs.
E2296829 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: Semau Island | Statement: [Sawusea, hasIsland, Semau 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: Semau Island
Triple: [Sawusea, hasIsland, Semau Island]
Generated description
Semau Island is a small Indonesian island located just off the western coast of Timor in East Nusa Tenggara Province, known for its traditional villages, dry landscapes, and surrounding coral reefs.

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_69eefaceb2a08190b9659b7f730629f5 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f62503d1c48190a6d75aa1e0775e33 completed May 2, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a82c183c08c8190b638197463e58444 completed Aug. 17, 2026, 8:08 a.m.
NEDg Description generation batch_6a82c2fae1ec8190ad4d34a3c9aed609 completed Aug. 17, 2026, 8:14 a.m.
NED2 Entity disambiguation (via description) batch_6a82c354fa4481908adcdcf3732a7c65 completed Aug. 17, 2026, 8:16 a.m.
Created at: April 27, 2026, 9:15 a.m.