Triple

T24649188
Position Surface form Disambiguated ID Type / Status
Subject Alphabetic Presentation Forms E610198 entity
Predicate compatibilityDecomposition P73433 FINISHED
Object many characters decompose to standard Hebrew letters 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: many characters decompose to standard Hebrew letters | Statement: [Alphabetic Presentation Forms, compatibilityDecomposition, many characters decompose to standard Hebrew letters]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: compatibilityDecomposition
Context triple: [Alphabetic Presentation Forms, compatibilityDecomposition, many characters decompose to standard Hebrew letters]
  • A. decomposesIn
    Indicates that one entity breaks down or separates into another entity or set of entities as its components or products.
  • B. hasDecomposition chosen
    Indicates that something can be broken down or separated into constituent parts, components, or simpler elements.
  • C. decompositionType
    Indicates the specific way in which a whole is broken down into its constituent parts or components.
  • D. yieldsDecomposition
    Indicates that one entity produces or results in a particular breakdown or decomposition of another entity.
  • E. projectionCompatibility
    Indicates that two or more projections (such as views, mappings, or representations) are mutually consistent and can be combined or used together without conflict.
  • 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_69e2c4d350a481909170482bc2ce6af9 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f44a417a58819081777e18dda149fd completed May 1, 2026, 6:37 a.m.
PD Predicate disambiguation batch_69f442a977b08190b44eac040cb90211 completed May 1, 2026, 6:05 a.m.
Created at: April 18, 2026, 2:33 a.m.