Triple

T24007777
Position Surface form Disambiguated ID Type / Status
Subject Cabrera Archipelago E594436 entity
Predicate hasIsland P970 FINISHED
Object Imperial Island
Imperial Island is one of the islands within the Cabrera Archipelago, a small, protected island group off the coast of Mallorca in Spain known for its natural and marine biodiversity.
E1660332 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: Imperial Island | Statement: [Cabrera Archipelago, hasIsland, Imperial 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: Imperial Island
Triple: [Cabrera Archipelago, hasIsland, Imperial Island]
Generated description
Imperial Island is one of the islands within the Cabrera Archipelago, a small, protected island group off the coast of Mallorca in Spain known for its natural and marine biodiversity.

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_69e288bc8f608190ac4af29f0bd1c744 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d46ba1f88190a204d8cfb0f64be6 completed April 29, 2026, 9:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048658cf88190b0fd6fcc517966f0 completed May 22, 2026, 12:13 p.m.
NEDg Description generation batch_6a1049149e648190803dd1d0fb8fb4a4 completed May 22, 2026, 12:16 p.m.
NED2 Entity disambiguation (via description) batch_6a1049becb848190b035eff19c6cd5ad completed May 22, 2026, 12:19 p.m.
Created at: April 17, 2026, 9:40 p.m.