Triple

T28824446
Position Surface form Disambiguated ID Type / Status
Subject Μορέας E727863 entity
Predicate hasSubregion P285 FINISHED
Object Μάνη
Η Μάνη είναι μια ιστορική και ορεινή περιοχή της νότιας Πελοποννήσου, γνωστή για τους πέτρινους πύργους, τα παραδοσιακά χωριά και τον ιδιαίτερο μανιάτικο πολιτισμό.
E1837684 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: Μάνη | Statement: [Μορέας, hasSubregion, Μάνη]
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: Μάνη
Triple: [Μορέας, hasSubregion, Μάνη]
Generated description
Η Μάνη είναι μια ιστορική και ορεινή περιοχή της νότιας Πελοποννήσου, γνωστή για τους πέτρινους πύργους, τα παραδοσιακά χωριά και τον ιδιαίτερο μανιάτικο πολιτισμό.

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_69f0319d09088190bbf14cdf1987792a completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f6593772ec8190805b9fabde7083f4 completed May 2, 2026, 8:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24bba70f0c8190a921a33a873969d9 completed June 7, 2026, 12:30 a.m.
NEDg Description generation batch_6a24bf95145c81908c8b06ac4c17c086 completed June 7, 2026, 12:47 a.m.
NED2 Entity disambiguation (via description) batch_6a24c40832a881908ca8c2d0b09b1458 completed June 7, 2026, 1:06 a.m.
Created at: April 28, 2026, 6:35 a.m.