Triple

T21989495
Position Surface form Disambiguated ID Type / Status
Subject UDDI E543045 entity
Predicate definesConcept P773 FINISHED
Object tModel NE NERFINISHED

How this triple was built (3 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: tModel | Statement: [UDDI, definesConcept, tModel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: tModel
Context triple: [UDDI, definesConcept, tModel]
  • A. T-Model
    The T-Model was an early leather football design used in top-level international competitions, including the inaugural FIFA World Cup.
  • B. T-Modell
    The T-Modell is the station wagon variant of Mercedes-Benz passenger cars, offering extended cargo space and practicality compared to the sedan versions.
  • C. Modell
    Modell is the surname of Art Modell, the influential former owner of the NFL’s Cleveland Browns and Baltimore Ravens.
  • D. Tucker model
    The Tucker model is a form of higher-order principal component analysis that decomposes a tensor into a core tensor multiplied by factor matrices along each mode, widely used for multi-way data analysis.
  • E. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: tModel
Target entity description: tModel is a UDDI data structure that provides a standardized, reusable description of technical specifications or service interfaces to enable consistent discovery and interoperability in web services registries.
  • A. T-Model
    The T-Model was an early leather football design used in top-level international competitions, including the inaugural FIFA World Cup.
  • B. T-Modell
    The T-Modell is the station wagon variant of Mercedes-Benz passenger cars, offering extended cargo space and practicality compared to the sedan versions.
  • C. Modell
    Modell is the surname of Art Modell, the influential former owner of the NFL’s Cleveland Browns and Baltimore Ravens.
  • D. Tucker model
    The Tucker model is a form of higher-order principal component analysis that decomposes a tensor into a core tensor multiplied by factor matrices along each mode, widely used for multi-way data analysis.
  • E. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • F. None of above. chosen

Provenance (2 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_69e0c48136b081908831fa907cc02e18 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1270cb67c81909a3aa2dc61c1894f completed April 28, 2026, 9:30 p.m.
Created at: April 16, 2026, 8:05 p.m.