Triple

T16966035
Position Surface form Disambiguated ID Type / Status
Subject ISO 19100 series E411540 entity
Predicate hasPart P35 FINISHED
Object ISO 19158 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: ISO 19158 | Statement: [ISO 19100 series, hasPart, ISO 19158]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ISO 19158
Context triple: [ISO 19100 series, hasPart, ISO 19158]
  • A. ISO 19157
    ISO 19157 is an international standard that defines principles and guidelines for describing, evaluating, and reporting the quality of geographic information and datasets.
  • B. ISO 19152
    ISO 19152 is an international standard that defines the Land Administration Domain Model (LADM) for representing and managing land-related rights, responsibilities, and spatial information.
  • C. ISO 19108
    ISO 19108 is an international standard that defines the temporal schema for geographic information, specifying how time is modeled and managed in geospatial datasets.
  • D. ISO 19156
    ISO 19156 is an international standard that defines a conceptual model for observations and measurements in geographic information systems, enabling consistent representation and exchange of observation data.
  • E. ISO 19148
    ISO 19148 is an international standard in the ISO 19100 geographic information series that defines a linear referencing system for locating geographic features along linear elements such as roads or pipelines.
  • 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: ISO 19158
Target entity description: ISO 19158 is an international standard within the ISO 19100 geographic information series that specifies a framework for quality assurance of data supply.
  • A. ISO 19157
    ISO 19157 is an international standard that defines principles and guidelines for describing, evaluating, and reporting the quality of geographic information and datasets.
  • B. ISO 19152
    ISO 19152 is an international standard that defines the Land Administration Domain Model (LADM) for representing and managing land-related rights, responsibilities, and spatial information.
  • C. ISO 19108
    ISO 19108 is an international standard that defines the temporal schema for geographic information, specifying how time is modeled and managed in geospatial datasets.
  • D. ISO 19156
    ISO 19156 is an international standard that defines a conceptual model for observations and measurements in geographic information systems, enabling consistent representation and exchange of observation data.
  • E. ISO 19148
    ISO 19148 is an international standard in the ISO 19100 geographic information series that defines a linear referencing system for locating geographic features along linear elements such as roads or pipelines.
  • 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_69d886c9c9d481909afe222093641cae completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d0a3cecc8190a490573adce80cca completed April 18, 2026, 6:42 p.m.
Created at: April 10, 2026, 5:31 a.m.