Triple

T29967601
Position Surface form Disambiguated ID Type / Status
Subject Insular Region of Ecuador E761230 entity
Predicate contains P35 FINISHED
Object Santa Fe Island
Santa Fe Island is a small, uninhabited island in Ecuador’s Galápagos archipelago, known for its unique wildlife such as land iguanas and its rugged, arid landscapes.
E1898633 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: Santa Fe Island | Statement: [Insular Region of Ecuador, contains, Santa Fe 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: Santa Fe Island
Triple: [Insular Region of Ecuador, contains, Santa Fe Island]
Generated description
Santa Fe Island is a small, uninhabited island in Ecuador’s Galápagos archipelago, known for its unique wildlife such as land iguanas and its rugged, arid 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_69f22467626081908d5afea489590e96 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6786bd7208190b8bb4aa26506f597 completed May 2, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a274306b99c8190b9427309f107cc9d completed June 8, 2026, 10:32 p.m.
NEDg Description generation batch_6a274402537c8190ade00dfc5d92e722 completed June 8, 2026, 10:36 p.m.
NED2 Entity disambiguation (via description) batch_6a2744f156208190b3617a3623b8b3ec completed June 8, 2026, 10:40 p.m.
Created at: April 29, 2026, 6:30 p.m.