Triple

T24523651
Position Surface form Disambiguated ID Type / Status
Subject Tolomako E606603 entity
Predicate spokenOn P27530 FINISHED
Object Santo Island
Santo Island is a major island in the Vanuatu archipelago in the South Pacific, known for its diverse indigenous cultures, languages, and tropical landscapes.
 E2293117 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: Santo Island | Statement: [Tolomako, spokenOn, Santo 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: Santo Island
Triple: [Tolomako, spokenOn, Santo Island]
Generated description
Santo Island is a major island in the Vanuatu archipelago in the South Pacific, known for its diverse indigenous cultures, languages, and tropical 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_69e2c4c85778819085f5da9af3569ad5 completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a87394988190b9805e838f16c08a completed April 30, 2026, 12:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7a6a61e0a4819099a1ceea987b67f5 completed Aug. 11, 2026, 12:18 a.m.
NEDg Description generation batch_6a7a6adfeb488190ae28278a47b67afb completed Aug. 11, 2026, 12:20 a.m.
NED2 Entity disambiguation (via description) batch_6a7a6b249800819093df0c10cf276740 completed Aug. 11, 2026, 12:21 a.m.
Created at: April 18, 2026, 2:25 a.m.