Triple

T28087408
Position Surface form Disambiguated ID Type / Status
Subject Mercedes Group of Islands E709863 entity
Predicate hasPart P35 FINISHED
Object Quinapaguian Island
Quinapaguian Island is one of the islands in the Mercedes Group off the coast of Camarines Norte in the Philippines, known for its beaches and coastal scenery.
E2297651 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: Quinapaguian Island | Statement: [Mercedes Group of Islands, hasPart, Quinapaguian 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: Quinapaguian Island
Triple: [Mercedes Group of Islands, hasPart, Quinapaguian Island]
Generated description
Quinapaguian Island is one of the islands in the Mercedes Group off the coast of Camarines Norte in the Philippines, known for its beaches and coastal scenery.

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_69ef9b7037f0819095bb90eaccbcaf32 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f640668a7481908d6ae20a347a6063 completed May 2, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a83bb70b4d8819098879297d4326cb8 completed Aug. 18, 2026, 1:54 a.m.
NEDg Description generation batch_6a83bbe17f888190a93b571ed690c814 completed Aug. 18, 2026, 1:56 a.m.
NED2 Entity disambiguation (via description) batch_6a83bc309ce081909bb0ad49da4fcf6e completed Aug. 18, 2026, 1:58 a.m.
Created at: April 27, 2026, 8:56 p.m.