Triple

T1049597
Position Surface form Disambiguated ID Type / Status
Subject Reading E22663 entity
Predicate economySpecialization P7347 FINISHED
Object information technology 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: information technology | Statement: [Reading, economySpecialization, information technology]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: economySpecialization
Context triple: [Reading, economySpecialization, information technology]
  • A. economyIncludes chosen
    Indicates that an economy encompasses, contains, or is composed of the specified component, sector, or element.
  • B. economicSectorSourceOfWealth
    Indicates that a particular economic sector is the primary source from which an entity derives its wealth or income.
  • C. economicAspect
    Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
  • D. economicFunction
    Indicates the role or purpose an entity serves within an economic system, such as how it contributes to production, distribution, or consumption of goods and services.
  • E. economicTrend
    Indicates the general direction or pattern of economic activity or conditions over a period of time.
  • 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8f28c7c8190b9ca3749666bcbf3 completed March 1, 2026, 10:08 p.m.
PD Predicate disambiguation batch_69a4b72e3e488190b768005ad647886b completed March 1, 2026, 10:01 p.m.
Created at: March 1, 2026, 7:42 p.m.