Triple

T13759693
Position Surface form Disambiguated ID Type / Status
Subject Sandy E330569 entity
Predicate hasPostalArea P920 FINISHED
Object SG E209989 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: SG | Statement: [Sandy, hasPostalArea, SG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SG
Context triple: [Sandy, hasPostalArea, SG]
  • A. SG
    SG is the vehicle registration code used on license plates for the Swiss canton of St. Gallen.
  • B. SG
    SG is the vehicle registration code used on license plates for Spain’s Segovia Province.
  • C. SG chosen
    SG is a postcode area in the United Kingdom covering parts of Hertfordshire and surrounding regions.
  • D. SG
    SG is the Secretariat-General of the European Commission, the central administrative body that supports the Commission’s work, coordination, and decision-making processes.
  • E. SG
    SG (Sanspareils Greenlands) is a prominent Indian sports equipment manufacturer best known for its high-quality cricket gear, including bats, balls, and protective equipment.
  • 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0223ab9081909db05334860405e0 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7a8606dbc8190b0f7c38583986141 completed May 3, 2026, 7:56 p.m.
Created at: April 9, 2026, 10:09 p.m.