Triple

T15320981
Position Surface form Disambiguated ID Type / Status
Subject Mastichochoria E366288 entity
Predicate hasVillage P4011 FINISHED
Object Fana
Fana is a small village located within the Mastichochoria region on the Greek island of Chios, known for its traditional mastic-producing settlements.
 E1150502 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: Fana | Statement: [Mastichochoria, hasVillage, Fana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fana
Context triple: [Mastichochoria, hasVillage, Fana]
  • A. Fana
    Fana is an Etruscan goddess, likely associated with nature, fertility, or sacred groves within the ancient Etruscan religious pantheon.
  • B. Fana
    Fana is a South African actor and politician known for his roles in films such as "Hotel Rwanda" and "World War Z."
  • C. Garango
    Garango is a town in Burkina Faso known for its cultural and municipal ties with the German town of Ladenburg.
  • D. Faya
    Faya is a town in northern Chad that serves as an important oasis and regional administrative center in the Sahara Desert.
  • E. Kinyara
    Kinyara is a town in Uganda’s Masindi District, best known for its large sugar estate and associated agro-industrial activities.
  • 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: Fana
Triple: [Mastichochoria, hasVillage, Fana]
Generated description
Fana is a small village located within the Mastichochoria region on the Greek island of Chios, known for its traditional mastic-producing settlements.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fana
Target entity description: Fana is a small village located within the Mastichochoria region on the Greek island of Chios, known for its traditional mastic-producing settlements.
  • A. Fana
    Fana is a South African actor and politician known for his roles in films such as "Hotel Rwanda" and "World War Z."
  • B. Fana
    Fana is an Etruscan goddess, likely associated with nature, fertility, or sacred groves within the ancient Etruscan religious pantheon.
  • C. Garango
    Garango is a town in Burkina Faso known for its cultural and municipal ties with the German town of Ladenburg.
  • D. Faya
    Faya is a town in northern Chad that serves as an important oasis and regional administrative center in the Sahara Desert.
  • E. Kinyara
    Kinyara is a town in Uganda’s Masindi District, best known for its large sugar estate and associated agro-industrial activities.
  • 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_69d85a121520819093dcce999fdefe1a completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03dd460288190b5c41f0a0aeee949 completed April 16, 2026, 1:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef8a9085881909904152c32b0fed1 completed May 9, 2026, 9:04 a.m.
NEDg Description generation batch_69fefc8251d08190bf8a764f83f89d7e completed May 9, 2026, 9:21 a.m.
NED2 Entity disambiguation (via description) batch_69fefd6c2bf88190b17a03be7b3353e3 completed May 9, 2026, 9:25 a.m.
Created at: April 10, 2026, 3:16 a.m.