Triple

T1622962
Position Surface form Disambiguated ID Type / Status
Subject Santpedor E35073 entity
Predicate hasCoordinateSystem P182 FINISHED
Object WGS84 E16682 NE 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: WGS84 | Statement: [Santpedor, hasCoordinateSystem, WGS84]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WGS84
Context triple: [Santpedor, hasCoordinateSystem, WGS84]
  • A. WGS84 chosen
    WGS84 is the global geodetic reference system and standard coordinate framework used for GPS and most modern mapping applications.
  • B. National Spatial Reference System
    The National Spatial Reference System is the official coordinate framework used in the United States to define precise locations, elevations, and boundaries for mapping, surveying, and navigation.
  • C. GLONASS
    GLONASS is Russia’s global satellite navigation system, providing worldwide positioning and timing services as an alternative to GPS.
  • D. GPS
    GPS (Global Positioning System) is a satellite-based navigation system that provides precise location and timing information to military and civilian users worldwide.
  • E. Differential GPS
    Differential GPS is an enhanced positioning system that improves the accuracy of standard GPS signals by using ground-based reference stations to correct signal errors.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a886023194819080a3fccd6e325d0e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909cf3c7481909ddbe6a6596bb0c8 completed March 5, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad6092fdd0819099bde0004de869c4 completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:28 p.m.