Triple

T15337265
Position Surface form Disambiguated ID Type / Status
Subject Phthiotis regional unit E366698 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object MI
MI is the vehicle registration code used on license plates for vehicles registered in the Phthiotis regional unit of Greece.
 E1150888 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: MI | Statement: [Phthiotis regional unit, vehicleRegistrationCode, MI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MI
Context triple: [Phthiotis regional unit, vehicleRegistrationCode, MI]
  • A. MI
    MI is the official two-letter United States Postal Service abbreviation for the state of Michigan.
  • B. MI
    MI is the commonly used abbreviation for the Mumbai Indians, a prominent franchise cricket team in the Indian Premier League.
  • C. MI
    MI is the vehicle registration code used on license plates for vehicles registered in Minden, a town in Germany.
  • D. MI
    MI is the Mathematical Institute of Leiden University, a department focused on research and education in mathematics.
  • E. Mi
    Mi was the ancestral clan name of the royal house of the ancient Chinese state of Chu, to which King Zhuang of Chu belonged.
  • 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: MI
Triple: [Phthiotis regional unit, vehicleRegistrationCode, MI]
Generated description
MI is the vehicle registration code used on license plates for vehicles registered in the Phthiotis regional unit of Greece.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MI
Target entity description: MI is the vehicle registration code used on license plates for vehicles registered in the Phthiotis regional unit of Greece.
  • A. MI
    MI is the official two-letter United States Postal Service abbreviation for the state of Michigan.
  • B. MI
    MI is the commonly used abbreviation for the Mumbai Indians, a prominent franchise cricket team in the Indian Premier League.
  • C. MI
    MI is the vehicle registration code used on license plates for vehicles registered in Minden, a town in Germany.
  • D. MI
    MI is the Mathematical Institute of Leiden University, a department focused on research and education in mathematics.
  • E. Mi
    Mi was the ancestral clan name of the royal house of the ancient Chinese state of Chu, to which King Zhuang of Chu belonged.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e11b22c81908280efe65acd5454 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01f11b88819089342e8b088bc95e completed May 9, 2026, 9:44 a.m.
NEDg Description generation batch_69ff02de46948190ac9b9f87313a8442 completed May 9, 2026, 9:48 a.m.
NED2 Entity disambiguation (via description) batch_69ff0341238c8190a7d0473ad9ab702c completed May 9, 2026, 9:49 a.m.
Created at: April 10, 2026, 3:17 a.m.