Triple

T4744118
Position Surface form Disambiguated ID Type / Status
Subject Mount Vermio E105317 entity
Predicate GreekName P3659 FINISHED
Object Βέρμιο
Βέρμιο είναι ορεινός όγκος της βόρειας Ελλάδας στη Δυτική και Κεντρική Μακεδονία, γνωστός για τα χιονοδρομικά του κέντρα και τα πλούσια δάση του.
 E465770 NE FINISHED

How this triple was built (4 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: Βέρμιο | Statement: [Mount Vermio, GreekName, Βέρμιο]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Βέρμιο
Context triple: [Mount Vermio, GreekName, Βέρμιο]
  • A. Vimioso
    Vimioso is a municipality in northeastern Portugal known for its strong cultural ties to the Mirandese language and traditional rural heritage.
  • B. Muscoy
    Muscoy is an unincorporated community in San Bernardino County, California, known for its semi-rural character within the Inland Empire region.
  • C. Cheremule
    Cheremule is a small municipality in northern Sardinia, Italy, known for its rural landscape and archaeological sites within the historical Logudoro region.
  • D. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • E. Moura
    Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Βέρμιο
Triple: [Mount Vermio, GreekName, Βέρμιο]
Generated description
Βέρμιο είναι ορεινός όγκος της βόρειας Ελλάδας στη Δυτική και Κεντρική Μακεδονία, γνωστός για τα χιονοδρομικά του κέντρα και τα πλούσια δάση του.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Βέρμιο
Target entity description: Βέρμιο είναι ορεινός όγκος της βόρειας Ελλάδας στη Δυτική και Κεντρική Μακεδονία, γνωστός για τα χιονοδρομικά του κέντρα και τα πλούσια δάση του.
  • A. Vimioso
    Vimioso is a municipality in northeastern Portugal known for its strong cultural ties to the Mirandese language and traditional rural heritage.
  • B. Muscoy
    Muscoy is an unincorporated community in San Bernardino County, California, known for its semi-rural character within the Inland Empire region.
  • C. Cheremule
    Cheremule is a small municipality in northern Sardinia, Italy, known for its rural landscape and archaeological sites within the historical Logudoro region.
  • D. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • E. Moura
    Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
  • F. None of above. chosen

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_69bd43ef87a48190a5bc3600711aa032 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64aa72c0819082ede0f531d75e65 completed March 20, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a37a77881909d32027f1ada99c5 completed March 21, 2026, 6:27 a.m.
NEDg Description generation batch_69be3b11371081908c028d7a1376f473 completed March 21, 2026, 6:30 a.m.
NED2 Entity disambiguation (via description) batch_69be3b8c77f88190aac16b6941fb5df7 completed March 21, 2026, 6:32 a.m.
Created at: March 20, 2026, 1:19 p.m.