Triple

T4744166
Position Surface form Disambiguated ID Type / Status
Subject Mount Pangaion E105318 entity
Predicate hasPeak P8205 FINISHED
Object Vigla
Vigla is a notable summit of Mount Pangaion in northern Greece, known for its mountainous terrain and scenic views.
 E465775 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: Vigla | Statement: [Mount Pangaion, hasPeak, Vigla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vigla
Context triple: [Mount Pangaion, hasPeak, Vigla]
  • A. Vingrau
    Vingrau is a small commune in southern France’s Pyrénées-Orientales department, known for its wine production and scenic location amid rugged limestone hills.
  • B. Vizzavona
    Vizzavona is a small mountain village and forested pass area in central Corsica, known as a key stop for hikers on the island’s famous GR20 trail.
  • C. Vlašim
    Vlašim is a small Czech town known for its historic château, English-style park, and location in the Central Bohemian Region southeast of Prague.
  • D. Luga
    Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
  • E. Viddalba
    Viddalba is a small town and comune in northern Sardinia, Italy, known for its rural setting and proximity to the Gallura region’s coastal and archaeological attractions.
  • 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: Vigla
Triple: [Mount Pangaion, hasPeak, Vigla]
Generated description
Vigla is a notable summit of Mount Pangaion in northern Greece, known for its mountainous terrain and scenic views.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vigla
Target entity description: Vigla is a notable summit of Mount Pangaion in northern Greece, known for its mountainous terrain and scenic views.
  • A. Vingrau
    Vingrau is a small commune in southern France’s Pyrénées-Orientales department, known for its wine production and scenic location amid rugged limestone hills.
  • B. Vizzavona
    Vizzavona is a small mountain village and forested pass area in central Corsica, known as a key stop for hikers on the island’s famous GR20 trail.
  • C. Vlašim
    Vlašim is a small Czech town known for its historic château, English-style park, and location in the Central Bohemian Region southeast of Prague.
  • D. Luga
    Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
  • E. Viddalba
    Viddalba is a small town and comune in northern Sardinia, Italy, known for its rural setting and proximity to the Gallura region’s coastal and archaeological attractions.
  • 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.