Triple

T37261212
Position Surface form Disambiguated ID Type / Status
Subject Σικελία E924261 entity
Predicate έχει μνημείο παγκόσμιας κληρονομιάς UNESCO P2499 FINISHED
Object Βίλα Ρομάνα ντελ Κασάλε
Η Βίλα Ρομάνα ντελ Κασάλε είναι μια πολυτελής ρωμαϊκή εξοχική κατοικία κοντά στο Πιάцца Αρμερίνα της Σικελίας, διάσημη για τα εξαιρετικά διατηρημένα ψηφιδωτά δάπεδά της.
E2218639 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: Βίλα Ρομάνα ντελ Κασάλε | Statement: [Σικελία, έχει μνημείο παγκόσμιας κληρονομιάς UNESCO, Βίλα Ρομάνα ντελ Κασάλε]
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: Βίλα Ρομάνα ντελ Κασάλε
Triple: [Σικελία, έχει μνημείο παγκόσμιας κληρονομιάς UNESCO, Βίλα Ρομάνα ντελ Κασάλε]
Generated description
Η Βίλα Ρομάνα ντελ Κασάλε είναι μια πολυτελής ρωμαϊκή εξοχική κατοικία κοντά στο Πιάцца Αρμερίνα της Σικελίας, διάσημη για τα εξαιρετικά διατηρημένα ψηφιδωτά δάπεδά της.

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_69fbbd1ac9e88190833f43d4d774ada8 completed May 6, 2026, 10:13 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.