Triple

T21869095
Position Surface form Disambiguated ID Type / Status
Subject Bixaceae E539957 entity
Predicate typeGenus P5980 FINISHED
Object Bixa
Bixa is a genus of tropical flowering plants best known for species like Bixa orellana, whose seeds produce the natural food coloring and dye annatto.
 E1504761 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: Bixa | Statement: [Bixaceae, typeGenus, Bixa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bixa
Context triple: [Bixaceae, typeGenus, Bixa]
  • A. Rubia
    Rubia is a genus of flowering plants in the coffee family known for species like madder, historically used as a source of red dye.
  • B. Sarraméa
    Sarraméa is a small inland commune in New Caledonia known for its lush mountainous landscapes and eco-tourism activities.
  • C. Damar
    Damar is a volcanic island in Indonesia’s Inner Banda Arc, known for its rugged terrain and relatively remote location in the Banda Sea.
  • D. Santal
    Santal are an indigenous ethnic group of South Asia, primarily found in India, Bangladesh, and Nepal, known for their distinct Austroasiatic language, rich oral traditions, and agrarian lifestyle.
  • E. Malanga
    Malanga is a surname most notably associated with Gerard Malanga, an American poet, photographer, and key collaborator of artist Andy Warhol.
  • 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: Bixa
Triple: [Bixaceae, typeGenus, Bixa]
Generated description
Bixa is a genus of tropical flowering plants best known for species like Bixa orellana, whose seeds produce the natural food coloring and dye annatto.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bixa
Target entity description: Bixa is a genus of tropical flowering plants best known for species like Bixa orellana, whose seeds produce the natural food coloring and dye annatto.
  • A. Rubia
    Rubia is a genus of flowering plants in the coffee family known for species like madder, historically used as a source of red dye.
  • B. Sarraméa
    Sarraméa is a small inland commune in New Caledonia known for its lush mountainous landscapes and eco-tourism activities.
  • C. Damar
    Damar is a volcanic island in Indonesia’s Inner Banda Arc, known for its rugged terrain and relatively remote location in the Banda Sea.
  • D. Santal
    Santal are an indigenous ethnic group of South Asia, primarily found in India, Bangladesh, and Nepal, known for their distinct Austroasiatic language, rich oral traditions, and agrarian lifestyle.
  • E. Malanga
    Malanga is a surname most notably associated with Gerard Malanga, an American poet, photographer, and key collaborator of artist Andy Warhol.
  • 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_69e0c478f59081909d54302b57fc1ce3 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f0f334362c819094af465ee57b47e6 completed April 28, 2026, 5:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a4be1b1148190a3d787fbae00f802 completed May 17, 2026, 11:14 p.m.
NEDg Description generation batch_6a0a4c9a02bc8190b285694c2710b825 completed May 17, 2026, 11:17 p.m.
NED2 Entity disambiguation (via description) batch_6a0a4d5d1b448190ba4387b0a3cc4285 completed May 17, 2026, 11:21 p.m.
Created at: April 16, 2026, 6:57 p.m.