Triple

T3259013
Position Surface form Disambiguated ID Type / Status
Subject Dorstenia E68365 entity
Predicate family P566 FINISHED
Object Moraceae E12373 NE FINISHED

How this triple was built (2 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: Moraceae | Statement: [Dorstenia, family, Moraceae]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moraceae
Context triple: [Dorstenia, family, Moraceae]
  • A. Moraceae chosen
    Moraceae is a family of flowering plants in the order Rosales that includes figs, mulberries, and breadfruit, many of which are known for their milky latex and economic importance.
  • B. Meliaceae
    Meliaceae is a family of mostly tropical flowering trees and shrubs that includes economically important timber and ornamental species such as mahogany and neem.
  • C. Cornaceae
    Cornaceae is a family of flowering plants best known for the dogwoods, which are mostly trees and shrubs found in temperate regions.
  • D. Sapindaceae
    Sapindaceae is a large family of flowering plants that includes many trees and shrubs such as maples, horse chestnuts, and lychees, known for their economic and ecological importance worldwide.
  • E. Malvaceae
    Malvaceae is a large family of flowering plants that includes mallows, hibiscus, cotton, and okra, many of which are important ornamentals and crops.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad858f74408190bcbd07f967cd7bd0 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adafa4f40c81909adfd0f7f568e3ce completed March 8, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bb1c468819083b50b5858f8afe0 completed March 12, 2026, 11:26 p.m.
Created at: March 8, 2026, 3:09 p.m.