Triple

T15832245
Position Surface form Disambiguated ID Type / Status
Subject Didi Dache E383898 entity
Predicate technology P1485 FINISHED
Object GPS E26827 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: GPS | Statement: [Didi Dache, technology, GPS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GPS
Context triple: [Didi Dache, technology, GPS]
  • A. GPS chosen
    GPS (Global Positioning System) is a satellite-based navigation system that provides precise location and timing information to military and civilian users worldwide.
  • B. GPS
    GPS is the Division of Geological and Planetary Sciences at the California Institute of Technology, focusing on research and education in Earth and planetary sciences.
  • C. GPS
    GPS is a professional school at the University of California San Diego specializing in international affairs, public policy, and global strategy.
  • D. GPS
    GPS is an early artificial intelligence program developed in the late 1950s to model human problem-solving by systematically searching for solutions in a defined problem space.
  • E. GPS
    GPS is the three-letter National Rail station code for Great Portland Street station on the London Underground network.
  • 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_69d86da34c888190976e06c4019d415a completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e11e653e388190a4696cdb22546715 completed April 16, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff999f9ccc8190bc859c2b78a16baf completed May 9, 2026, 8:31 p.m.
Created at: April 10, 2026, 4:49 a.m.