Triple

T37261184
Position Surface form Disambiguated ID Type / Status
Subject Σικελία E924261 entity
Predicate έχει ηφαίστειο P6356 FINISHED
Object Στρόμπολι
Η Στρόμπολι είναι ένα από τα πιο ενεργά ηφαίστεια της Ευρώπης, γνωστό για τις συχνές εκρήξεις του που είναι ορατές από μεγάλη απόσταση.
E2218631 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: Στρόμπολι | Statement: [Σικελία, έχει ηφαίστειο, Στρόμπολι]
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: Στρόμπολι
Triple: [Σικελία, έχει ηφαίστειο, Στρόμπολι]
Generated description
Η Στρόμπολι είναι ένα από τα πιο ενεργά ηφαίστεια της Ευρώπης, γνωστό για τις συχνές εκρήξεις του που είναι ορατές από μεγάλη απόσταση.

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_69f76eabd6c481909d414a80a1345c98 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbadf84c048190a131d9ef33d3c667 completed May 6, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4043d8d2e481908c363980e133e824 completed June 27, 2026, 9:42 p.m.
NEDg Description generation batch_6a40448854a88190852646c14a8f9864 completed June 27, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_6a404505b4048190bfadd456a3214fe1 completed June 27, 2026, 9:47 p.m.
Created at: May 3, 2026, 4:15 p.m.