Triple

T9716741
Position Surface form Disambiguated ID Type / Status
Subject Etruscan religion E235160 entity
Predicate hasDeity P5606 FINISHED
Object Fana
Fana is an Etruscan goddess, likely associated with nature, fertility, or sacred groves within the ancient Etruscan religious pantheon.
 E816005 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: [Etruscan religion, hasDeity, Fana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fana
Context triple: [Etruscan religion, hasDeity, Fana]
  • 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. Kwaluudhi
    Kwaluudhi is a dialect of the Ovambo language spoken by a specific Ovambo subgroup in northern Namibia.
  • C. Baafira
    Baafira is a popular dancehall/reggae song by Ghanaian artist Stonebwoy that helped boost his prominence in the African music scene.
  • D. Qunya
    Qunya is a historic town in central Anatolia, in present-day Turkey, known as the birthplace of the prominent Sufi philosopher Sadr al-Din al-Qunawi.
  • E. Xola
    Xola is a Mexico City Metro station on Line 2 that serves the southern part of the city near the Calzada de Tlalpan corridor.
  • 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: [Etruscan religion, hasDeity, Fana]
Generated description
Fana is an Etruscan goddess, likely associated with nature, fertility, or sacred groves within the ancient Etruscan religious pantheon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fana
Target entity description: Fana is an Etruscan goddess, likely associated with nature, fertility, or sacred groves within the ancient Etruscan religious pantheon.
  • 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. Kwaluudhi
    Kwaluudhi is a dialect of the Ovambo language spoken by a specific Ovambo subgroup in northern Namibia.
  • C. Baafira
    Baafira is a popular dancehall/reggae song by Ghanaian artist Stonebwoy that helped boost his prominence in the African music scene.
  • D. Qunya
    Qunya is a historic town in central Anatolia, in present-day Turkey, known as the birthplace of the prominent Sufi philosopher Sadr al-Din al-Qunawi.
  • E. Xola
    Xola is a Mexico City Metro station on Line 2 that serves the southern part of the city near the Calzada de Tlalpan corridor.
  • 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_69ca84cd8fa0819090a5e243ceb37003 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e3d75e08190b4d86363595bd40d completed April 1, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19f941b908190a3e27f4b6c1b3535 completed April 4, 2026, 11:32 p.m.
NEDg Description generation batch_69d1a00eafc08190a2be7684fd7e9320 completed April 4, 2026, 11:34 p.m.
NED2 Entity disambiguation (via description) batch_69d1a072e08c8190a3beaf1219fa850f completed April 4, 2026, 11:36 p.m.
Created at: March 30, 2026, 8:20 p.m.