Triple

T947195
Position Surface form Disambiguated ID Type / Status
Subject Heidenheim an der Brenz E20438 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object HDH
HDH is the vehicle registration code used on license plates for the German town of Heidenheim an der Brenz.
 E111221 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: HDH | Statement: [Heidenheim an der Brenz, vehicleRegistrationCode, HDH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HDH
Context triple: [Heidenheim an der Brenz, vehicleRegistrationCode, HDH]
  • A. DHE
    DHE is the Massachusetts state agency responsible for coordinating and overseeing public higher education institutions and policies.
  • B. CHH
    CHH is the vehicle registration code used on license plates for the Mexican state of Chihuahua.
  • C. HAA
    HAA is the Harvard Alumni Association, the organization that connects and serves Harvard University’s global community of alumni.
  • D. HH
    HH is the vehicle registration code used on license plates for the German city-state of Hamburg.
  • E. NDH
    NDH was the fascist puppet state established by the Axis powers in World War II on the territory of occupied Croatia and Bosnia and Herzegovina.
  • 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: HDH
Triple: [Heidenheim an der Brenz, vehicleRegistrationCode, HDH]
Generated description
HDH is the vehicle registration code used on license plates for the German town of Heidenheim an der Brenz.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HDH
Target entity description: HDH is the vehicle registration code used on license plates for the German town of Heidenheim an der Brenz.
  • A. DHE
    DHE is the Massachusetts state agency responsible for coordinating and overseeing public higher education institutions and policies.
  • B. CHH
    CHH is the vehicle registration code used on license plates for the Mexican state of Chihuahua.
  • C. HAA
    HAA is the Harvard Alumni Association, the organization that connects and serves Harvard University’s global community of alumni.
  • D. HH
    HH is the vehicle registration code used on license plates for the German city-state of Hamburg.
  • E. NDH
    NDH was the fascist puppet state established by the Axis powers in World War II on the territory of occupied Croatia and Bosnia and Herzegovina.
  • 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_69a493b0f2fc81908cd227480a5356a1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3be19448190a8863fce3d152430 completed March 1, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a826e7d55c8190b9b871caead76733 completed March 4, 2026, 12:34 p.m.
NEDg Description generation batch_69a845a793e08190892fe1a545095f62 completed March 4, 2026, 2:45 p.m.
NED2 Entity disambiguation (via description) batch_69a8463631608190a9ada5605e9625aa completed March 4, 2026, 2:48 p.m.
Created at: March 1, 2026, 7:40 p.m.