Triple

T6333391
Position Surface form Disambiguated ID Type / Status
Subject Excoecaria agallocha E142433 entity
Predicate latexEffect P70908 FINISHED
Object irritant to skin and eyes 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: irritant to skin and eyes | Statement: [Excoecaria agallocha, latexEffect, irritant to skin and eyes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: latexEffect
Context triple: [Excoecaria agallocha, latexEffect, irritant to skin and eyes]
  • A. visualEffect
    Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
  • B. projectionEffect
    Indicates the visual or spatial transformation produced when something is projected from one surface, medium, or viewpoint onto another.
  • C. latexType
    Indicates that one entity specifies or classifies the LaTeX formatting or representation type associated with another entity.
  • D. specialEffectsBy
    Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or entity.
  • E. eventEffect
    Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
  • F. None of above. chosen

Provenance (4 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_69c008d4d8e88190ad301c05b08722ac completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06517a1e88190a0bfcac8a7e3a305 completed March 22, 2026, 9:54 p.m.
PD Predicate disambiguation batch_69c060e7e2d48190af9d004236466788 completed March 22, 2026, 9:36 p.m.
PDg Predicate description generation batch_69c064c080148190a7c3218867f1f572 completed March 22, 2026, 9:53 p.m.
Created at: March 22, 2026, 4:30 p.m.