Triple

T8604089
Position Surface form Disambiguated ID Type / Status
Subject Donauwörth E203753 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object DON
DON is the vehicle registration code used on license plates for vehicles registered in the Donauwörth area of Germany.
 E744927 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: DON | Statement: [Donauwörth, vehicleRegistrationCode, DON]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DON
Context triple: [Donauwörth, vehicleRegistrationCode, DON]
  • A. Dani
    Dani is a fictional character played by actress Adria Arjona, known from her role in the fantasy-romance film "Emerald City" and other screen appearances.
  • B. Dani
    Dani is the given name of Dani Rodrik, a prominent Turkish economist known for his work on globalization and economic development.
  • C. Dani
    The Dani are an indigenous ethnic group of the central highlands of Papua, Indonesia, known for their distinctive traditional dress, terraced agriculture, and complex ritual practices.
  • D. Van
    Van is a historic city in eastern Anatolia, known as a major cultural and political center of ancient and medieval Armenian civilization on the shores of Lake Van.
  • E. Da
    Da was the personal given name of Emperor Zhang, a ruler of the Eastern Han dynasty in ancient China.
  • 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: DON
Triple: [Donauwörth, vehicleRegistrationCode, DON]
Generated description
DON is the vehicle registration code used on license plates for vehicles registered in the Donauwörth area of Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DON
Target entity description: DON is the vehicle registration code used on license plates for vehicles registered in the Donauwörth area of Germany.
  • A. Dani
    Dani is a fictional character played by actress Adria Arjona, known from her role in the fantasy-romance film "Emerald City" and other screen appearances.
  • B. Dani
    Dani is the given name of Dani Rodrik, a prominent Turkish economist known for his work on globalization and economic development.
  • C. Dani
    The Dani are an indigenous ethnic group of the central highlands of Papua, Indonesia, known for their distinctive traditional dress, terraced agriculture, and complex ritual practices.
  • D. Van
    Van is a historic city in eastern Anatolia, known as a major cultural and political center of ancient and medieval Armenian civilization on the shores of Lake Van.
  • E. Da
    Da was the personal given name of Emperor Zhang, a ruler of the Eastern Han dynasty in ancient China.
  • 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_69ca832b56948190ba751cec255308f1 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46dd8ff8819081ef269192047488 completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8f8dfa4819080c8ed475a84be41 completed April 2, 2026, 5:35 p.m.
NEDg Description generation batch_69cea9d0dad0819095134f6f8cafb4c0 completed April 2, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_69ceaa7025388190a3f17aca46d4858e completed April 2, 2026, 5:42 p.m.
Created at: March 30, 2026, 6:24 p.m.