Triple

T18712550
Position Surface form Disambiguated ID Type / Status
Subject Seychelles fody E457553 entity
Predicate foundOnIsland P35221 FINISHED
Object Frégate Island
Frégate Island is a small, privately owned granitic island in the Seychelles renowned for its luxury eco-resort and rich biodiversity, including several rare and endemic species.
E1610112 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: Frégate Island | Statement: [Seychelles fody, foundOnIsland, Frégate 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: Frégate Island
Triple: [Seychelles fody, foundOnIsland, Frégate Island]
Generated description
Frégate Island is a small, privately owned granitic island in the Seychelles renowned for its luxury eco-resort and rich biodiversity, including several rare and endemic species.

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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5671c53988190bfc132c853cebd02 completed April 19, 2026, 11:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0f75dd5dbc8190a66f635100414440 completed May 21, 2026, 9:15 p.m.
NEDg Description generation batch_6a0f76f167d08190a9e4d3abc3cc4545 completed May 21, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_6a0f78c015108190bb84972406f84239 completed May 21, 2026, 9:27 p.m.
Created at: April 10, 2026, 11:50 a.m.