Triple

T10643039
Position Surface form Disambiguated ID Type / Status
Subject Meadow Mari E250769 entity
Predicate ISO639-3 P208 FINISHED
Object mhr
mhr is the ISO 639-3 code for Meadow Mari, a Uralic language spoken primarily in the Mari El Republic of Russia.
 E877904 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: mhr | Statement: [Meadow Mari, ISO639-3, mhr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: mhr
Context triple: [Meadow Mari, ISO639-3, mhr]
  • A. MRH
    MRH is the IATA airport code for Michael J. Smith Field, a public airport serving Beaufort, North Carolina, in the United States.
  • B. MR
    MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
  • C. MR
    MR is the official vehicle registration code used on license plates for the city of Marburg in the German state of Hesse.
  • D. MH
    MH is the two-letter ISO 3166-1 alpha-2 country code representing the Republic of the Marshall Islands.
  • E. MH
    MH is the two-letter IATA airline designator used to identify Malaysia Airlines on tickets, timetables, and flight numbers.
  • 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: mhr
Triple: [Meadow Mari, ISO639-3, mhr]
Generated description
mhr is the ISO 639-3 code for Meadow Mari, a Uralic language spoken primarily in the Mari El Republic of Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: mhr
Target entity description: mhr is the ISO 639-3 code for Meadow Mari, a Uralic language spoken primarily in the Mari El Republic of Russia.
  • A. MRH
    MRH is the IATA airport code for Michael J. Smith Field, a public airport serving Beaufort, North Carolina, in the United States.
  • B. MR
    MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
  • C. MR
    MR is the official vehicle registration code used on license plates for the city of Marburg in the German state of Hesse.
  • D. MH
    MH is the two-letter ISO 3166-1 alpha-2 country code representing the Republic of the Marshall Islands.
  • E. MH
    MH is the two-letter IATA airline designator used to identify Malaysia Airlines on tickets, timetables, and flight numbers.
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfcf65fc81909a0c86daefaab1ab completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69d97a4555e48190be39c0a7698b4282 completed April 10, 2026, 10:31 p.m.
NEDg Description generation batch_69d97cc07100819088683a0d79b2baa0 completed April 10, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69d97e0cda0c8190af5013b971b2ad3c completed April 10, 2026, 10:47 p.m.
Created at: April 8, 2026, 9:05 p.m.