Triple

T2317462
Position Surface form Disambiguated ID Type / Status
Subject Goslar E51097 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object GS
GS is the vehicle registration code used on license plates for the district of Goslar in Lower Saxony, Germany.
 E256505 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: GS | Statement: [Goslar, vehicleRegistrationCode, GS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GS
Context triple: [Goslar, vehicleRegistrationCode, GS]
  • A. GS
    GS is the two-letter ISO 3166 country code assigned to the British Overseas Territory of South Georgia and the South Sandwich Islands in the southern Atlantic Ocean.
  • B. GD
    GD is the vehicle registration code used on license plates for cars registered in the city of Gdańsk, Poland.
  • C. GD
    GD is the stock ticker symbol for General Dynamics, a major American aerospace and defense corporation.
  • D. 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.
  • E. SG
    SG is a postcode area in the United Kingdom covering parts of Hertfordshire and surrounding regions.
  • 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: GS
Triple: [Goslar, vehicleRegistrationCode, GS]
Generated description
GS is the vehicle registration code used on license plates for the district of Goslar in Lower Saxony, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GS
Target entity description: GS is the vehicle registration code used on license plates for the district of Goslar in Lower Saxony, Germany.
  • A. GS
    GS is the two-letter ISO 3166 country code assigned to the British Overseas Territory of South Georgia and the South Sandwich Islands in the southern Atlantic Ocean.
  • B. GD
    GD is the vehicle registration code used on license plates for cars registered in the city of Gdańsk, Poland.
  • C. GD
    GD is the stock ticker symbol for General Dynamics, a major American aerospace and defense corporation.
  • D. 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.
  • E. SG
    SG is a postcode area in the United Kingdom covering parts of Hertfordshire and surrounding regions.
  • 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_69a88b074b908190ae983dbca7757d88 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc62df2048190ac7a5ebc0a4139b2 completed March 7, 2026, 6:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae8964902081909070dd03ccb7cf1f completed March 9, 2026, 8:48 a.m.
NEDg Description generation batch_69ae8ab5bf78819085120418a26cbe28 completed March 9, 2026, 8:54 a.m.
NED2 Entity disambiguation (via description) batch_69ae8b2a89788190975ab66f432f834f completed March 9, 2026, 8:56 a.m.
Created at: March 4, 2026, 7:49 p.m.