Triple

T656487
Position Surface form Disambiguated ID Type / Status
Subject Modern Standard Arabic E11660 entity
Predicate alsoKnownAs P39 FINISHED
Object MSA
MSA is the standardized, literary form of Arabic used in formal writing, media, education, and official communication across the Arab world.
 E82098 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: MSA | Statement: [Modern Standard Arabic, alsoKnownAs, MSA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MSA
Context triple: [Modern Standard Arabic, alsoKnownAs, MSA]
  • A. MSA
    MSA is the common abbreviation for the Master Settlement Agreement, a landmark 1998 legal settlement between major U.S. tobacco companies and state attorneys general that reshaped tobacco advertising and funded public health initiatives.
  • B. MSK
    MSK is the standard time zone abbreviation used for Moscow Time, which is three hours ahead of Coordinated Universal Time (UTC+3).
  • C. MS
    MS is the official two-letter United States Postal Service abbreviation for the state of Mississippi.
  • D. MPS
    MPS is a leading German research institute specializing in the study of the Sun and the solar system, operating under the Max Planck Society.
  • E. MSP
    MSP is the primary statewide law enforcement agency responsible for highway patrol, criminal investigations, and public safety across the Commonwealth of Massachusetts.
  • 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: MSA
Triple: [Modern Standard Arabic, alsoKnownAs, MSA]
Generated description
MSA is the standardized, literary form of Arabic used in formal writing, media, education, and official communication across the Arab world.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MSA
Target entity description: MSA is the standardized, literary form of Arabic used in formal writing, media, education, and official communication across the Arab world.
  • A. MSA
    MSA is the common abbreviation for the Master Settlement Agreement, a landmark 1998 legal settlement between major U.S. tobacco companies and state attorneys general that reshaped tobacco advertising and funded public health initiatives.
  • B. MSK
    MSK is the standard time zone abbreviation used for Moscow Time, which is three hours ahead of Coordinated Universal Time (UTC+3).
  • C. MS
    MS is the official two-letter United States Postal Service abbreviation for the state of Mississippi.
  • D. MPS
    MPS is a leading German research institute specializing in the study of the Sun and the solar system, operating under the Max Planck Society.
  • E. MSP
    MSP is the primary statewide law enforcement agency responsible for highway patrol, criminal investigations, and public safety across the Commonwealth of Massachusetts.
  • 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_69a4932862a0819098be659c814e4981 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f4e87408190b5276d2b913d0426 completed March 1, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5914abe2c8190a27f520f445554d8 completed March 2, 2026, 1:31 p.m.
NEDg Description generation batch_69a5ab066d348190bbe5956cce0407ef completed March 2, 2026, 3:21 p.m.
NED2 Entity disambiguation (via description) batch_69a5c240eebc819098cd79447ed95b08 completed March 2, 2026, 5 p.m.
Created at: March 1, 2026, 7:36 p.m.