Triple

T1242690
Position Surface form Disambiguated ID Type / Status
Subject Kent mango E26692 entity
Predicate diseaseSusceptibility P583 FINISHED
Object anthracnose susceptible LITERAL 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: anthracnose susceptible | Statement: [Kent mango, diseaseSusceptibility, anthracnose susceptible]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: diseaseSusceptibility
Context triple: [Kent mango, diseaseSusceptibility, anthracnose susceptible]
  • A. diseaseResistance
    Indicates how effectively one entity can prevent, withstand, or recover from harmful effects caused by a particular disease or pathogen in relation to another.
  • B. diseaseType
    Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
  • C. hasTargetDisease
    Indicates that an entity (such as a treatment, study, or intervention) is directed toward, intended to affect, or primarily concerned with a specified disease.
  • D. geneticInfluence
    Indicates that one entity affects or contributes to the genetic traits, characteristics, or heredity of another entity.
  • E. susceptibleTo chosen
    Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
  • F. None of above.

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_69a4948689d08190b3a4a3f388c02148 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf61fadc8190b7b9e23eaa15a61d completed March 1, 2026, 10:36 p.m.
PD Predicate disambiguation batch_69a4bb696a38819095845c84f0241287 completed March 1, 2026, 10:19 p.m.
Created at: March 1, 2026, 7:47 p.m.