Triple

T1222135
Position Surface form Disambiguated ID Type / Status
Subject Gujarati script E26244 entity
Predicate visualFeature P25983 FINISHED
Object rounded letterforms compared to Devanagari 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: rounded letterforms compared to Devanagari | Statement: [Gujarati script, visualFeature, rounded letterforms compared to Devanagari]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: visualFeature
Context triple: [Gujarati script, visualFeature, rounded letterforms compared to Devanagari]
  • A. vision
    Indicates that an entity perceives another entity or object visually, using sight.
  • B. facesChallenge
    Indicates that an entity is confronted with a difficulty, obstacle, or demanding situation that must be dealt with or overcome.
  • C. faceValueType
    Indicates the type or category of a financial instrument’s face (nominal) value, such as how that value is defined or represented.
  • D. mediaDepictionAs
    Indicates that one entity is portrayed or represented as another entity or in a particular way within some medium (e.g., image, film, text).
  • E. viewOnEmotion
    Indicates a relationship where one entity holds a particular emotional perspective, reaction, or attitude toward another entity or situation.
  • 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_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be21a2bc819094b47580d7c5cdf8 completed March 1, 2026, 10:30 p.m.
PD Predicate disambiguation batch_69a4bb644af08190ba25905f20adb01a completed March 1, 2026, 10:19 p.m.
PDg Predicate description generation batch_69a4bd3140688190ac6e24de157fd61e completed March 1, 2026, 10:26 p.m.
Created at: March 1, 2026, 7:47 p.m.