Triple

T34478218
Position Surface form Disambiguated ID Type / Status
Subject Hoorn Islands E885104 entity
Predicate formerName P65 FINISHED
Object Islas de Hornos
Islas de Hornos is the former Spanish name for the Hoorn Islands, a small group of islands in the South Pacific that are part of Wallis and Futuna, a French overseas collectivity.
E2098597 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: Islas de Hornos | Statement: [Hoorn Islands, formerName, Islas de Hornos]
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: Islas de Hornos
Triple: [Hoorn Islands, formerName, Islas de Hornos]
Generated description
Islas de Hornos is the former Spanish name for the Hoorn Islands, a small group of islands in the South Pacific that are part of Wallis and Futuna, a French overseas collectivity.

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_69f349c880408190ade571c471ab154a completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71ccc90b081908ae1b9a5dcb69d7b completed May 3, 2026, 10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a372135fcb8819096033e159f5db7ac completed June 20, 2026, 11:24 p.m.
NEDg Description generation batch_6a37221583e48190a3dbe0dc7ad27453 completed June 20, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_6a3722b425808190a8453a3e71d14066 completed June 20, 2026, 11:31 p.m.
Created at: May 1, 2026, 2:01 a.m.