Triple

T8292368
Position Surface form Disambiguated ID Type / Status
Subject Homburg vor der Höhe E193929 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object HG
HG is the vehicle registration code used on license plates for the German town of Homburg vor der Höhe and its surrounding district.
 E723504 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: HG | Statement: [Homburg vor der Höhe, vehicleRegistrationCode, HG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HG
Context triple: [Homburg vor der Höhe, vehicleRegistrationCode, HG]
  • A. HG
    HG is the postcode area designation covering Harrogate and surrounding parts of North Yorkshire, England.
  • B. HQ
    HQ is the commonly used abbreviation for Hydro-Québec, the provincial government–owned electric utility serving Quebec, Canada.
  • C. GN
    GN is a fast, meta-build system tool used primarily by the Chromium project to generate build files for Ninja.
  • D. HGS
    HGS is the National Rail station code assigned to Hastings railway station in East Sussex, England.
  • E. HL
    HL is the vehicle registration code used on license plates for the German city of Lübeck.
  • 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: HG
Triple: [Homburg vor der Höhe, vehicleRegistrationCode, HG]
Generated description
HG is the vehicle registration code used on license plates for the German town of Homburg vor der Höhe and its surrounding district.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HG
Target entity description: HG is the vehicle registration code used on license plates for the German town of Homburg vor der Höhe and its surrounding district.
  • A. HG
    HG is the postcode area designation covering Harrogate and surrounding parts of North Yorkshire, England.
  • B. HQ
    HQ is the commonly used abbreviation for Hydro-Québec, the provincial government–owned electric utility serving Quebec, Canada.
  • C. GN
    GN is a fast, meta-build system tool used primarily by the Chromium project to generate build files for Ninja.
  • D. HGS
    HGS is the National Rail station code assigned to Hastings railway station in East Sussex, England.
  • E. HL
    HL is the vehicle registration code used on license plates for the German city of Lübeck.
  • 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_69ca82e32db481908b72f3804fa71152 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7c9ccbfc81908825685c23b80d23 completed March 31, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd68916c5481908c42f259298b0670 completed April 1, 2026, 6:48 p.m.
NEDg Description generation batch_69cd6d567c3c81908a7ec5bc13be529d completed April 1, 2026, 7:09 p.m.
NED2 Entity disambiguation (via description) batch_69cd7e3e2f848190a22ad8739bb8e298 completed April 1, 2026, 8:21 p.m.
Created at: March 30, 2026, 5:52 p.m.