Triple

T3533569
Position Surface form Disambiguated ID Type / Status
Subject Meissen E74716 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object MEI
MEI is the vehicle registration code for the German town of Meissen in the state of Saxony.
 E364510 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: MEI | Statement: [Meissen, hasVehicleRegistrationCode, MEI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MEI
Context triple: [Meissen, hasVehicleRegistrationCode, MEI]
  • A. MEEI
    MEEI is a renowned specialty hospital in Boston focused on ophthalmology and otolaryngology, affiliated with Harvard Medical School.
  • B. MEC
    MEC is the commonly used acronym for Uruguay’s Ministry of Education and Culture, the national body responsible for educational policy and cultural affairs.
  • C. mye
    mye is the ISO 639-3 language code for Myene, a Bantu language spoken primarily along the coast of Gabon.
  • D. MI
    MI is the official two-letter United States Postal Service abbreviation for the state of Michigan.
  • E. MAI
    MAI is the commonly used abbreviation for Romania’s Ministry of Internal Affairs, the government body responsible for internal security, public order, and civil administration.
  • 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: MEI
Triple: [Meissen, hasVehicleRegistrationCode, MEI]
Generated description
MEI is the vehicle registration code for the German town of Meissen in the state of Saxony.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MEI
Target entity description: MEI is the vehicle registration code for the German town of Meissen in the state of Saxony.
  • A. MEEI
    MEEI is a renowned specialty hospital in Boston focused on ophthalmology and otolaryngology, affiliated with Harvard Medical School.
  • B. MEC
    MEC is the commonly used acronym for Uruguay’s Ministry of Education and Culture, the national body responsible for educational policy and cultural affairs.
  • C. mye
    mye is the ISO 639-3 language code for Myene, a Bantu language spoken primarily along the coast of Gabon.
  • D. MI
    MI is the official two-letter United States Postal Service abbreviation for the state of Michigan.
  • E. MAI
    MAI is the commonly used abbreviation for Romania’s Ministry of Internal Affairs, the government body responsible for internal security, public order, and civil administration.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc9b945481909867d44b810e8b1f completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e9c408481909a808d400f545ff8 completed March 13, 2026, 3:03 a.m.
NEDg Description generation batch_69b37f232b8881908f7b4df89399d1d8 completed March 13, 2026, 3:06 a.m.
NED2 Entity disambiguation (via description) batch_69b37f8fea9481909eb82a06e6c71e98 completed March 13, 2026, 3:08 a.m.
Created at: March 8, 2026, 3:19 p.m.