Triple

T9205667
Position Surface form Disambiguated ID Type / Status
Subject Trenggalek E220969 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object AG
AG is an Indonesian vehicle registration code used for motor vehicles registered in certain regions of East Java, including Trenggalek.
 E785861 NE FINISHED

How this triple was built (4 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: AG | Statement: [Trenggalek, hasVehicleRegistrationCode, AG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: AG
Context triple: [Trenggalek, hasVehicleRegistrationCode, AG]
  • A. AG
    AG is the two-letter ISO 3166-1 alpha-2 country code assigned to Antigua and Barbuda.
  • B. AG
    AG is the vehicle registration code used on license plates for cars registered in Argeș County, Romania.
  • C. AG
    AG is the common abbreviation for the Christian missions organization To the Nations.
  • D. AG
    AG is the standard abbreviation for the United States Attorney General, the chief law enforcement officer and head of the U.S. Department of Justice.
  • E. GU
    GU is the two-letter ISO 3166 country code assigned to Guam, an unincorporated territory of the United States in the western Pacific Ocean.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: AG
Triple: [Trenggalek, hasVehicleRegistrationCode, AG]
Generated description
AG is an Indonesian vehicle registration code used for motor vehicles registered in certain regions of East Java, including Trenggalek.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: AG
Target entity description: AG is an Indonesian vehicle registration code used for motor vehicles registered in certain regions of East Java, including Trenggalek.
  • A. AG
    AG is the standard abbreviation for the United States Attorney General, the chief law enforcement officer and head of the U.S. Department of Justice.
  • B. AG
    AG is the two-letter ISO 3166-1 alpha-2 country code assigned to Antigua and Barbuda.
  • C. AG
    AG is the vehicle registration code used on license plates for cars registered in Argeș County, Romania.
  • D. AG
    AG is the common abbreviation for the Christian missions organization To the Nations.
  • E. GU
    GU is the two-letter ISO 3166 country code assigned to Guam, an unincorporated territory of the United States in the western Pacific Ocean.
  • F. None of above. chosen

Provenance (5 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_69ca83e8e9248190862cf3e41693b310 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd947a0a08190966f22a6207c9120 completed April 1, 2026, 8:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69d065e09fbc81908159b386038b3d73 completed April 4, 2026, 1:14 a.m.
NEDg Description generation batch_69d0676ea53c81908b16dfce6810f6b0 completed April 4, 2026, 1:20 a.m.
NED2 Entity disambiguation (via description) batch_69d0684c1a108190bc7fdfdced16e24c completed April 4, 2026, 1:24 a.m.
Created at: March 30, 2026, 7:26 p.m.