Triple

T277323
Position Surface form Disambiguated ID Type / Status
Subject Power BI E5276 entity
Predicate programmingLanguage P1592 FINISHED
Object DAX
DAX (Data Analysis Expressions) is a formula and query language used in Microsoft Power BI, Excel Power Pivot, and Analysis Services for creating custom calculations and data models.
 E35616 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: DAX | Statement: [Power BI, programmingLanguage, DAX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DAX
Context triple: [Power BI, programmingLanguage, DAX]
  • A. DAX
    DAX is Germany’s leading blue-chip stock market index, tracking the performance of major companies listed on the Frankfurt Stock Exchange.
  • B. DAL
    DAL is the stock ticker symbol for Delta Air Lines, a major U.S.-based international airline.
  • C. DCA
    DCA (Defense Communications Agency) was a U.S. Department of Defense organization responsible for managing and overseeing military communications networks, including early internet precursor systems.
  • D. DCA
    DCA is the three-letter IATA airport code for Ronald Reagan Washington National Airport, the primary domestic airport serving Washington, D.C.
  • E. AEX index
    The AEX index is a benchmark stock market index that tracks the performance of the largest and most actively traded companies listed on the Amsterdam Stock Exchange.
  • 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: DAX
Triple: [Power BI, programmingLanguage, DAX]
Generated description
DAX (Data Analysis Expressions) is a formula and query language used in Microsoft Power BI, Excel Power Pivot, and Analysis Services for creating custom calculations and data models.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DAX
Target entity description: DAX (Data Analysis Expressions) is a formula and query language used in Microsoft Power BI, Excel Power Pivot, and Analysis Services for creating custom calculations and data models.
  • A. DAX
    DAX is Germany’s leading blue-chip stock market index, tracking the performance of major companies listed on the Frankfurt Stock Exchange.
  • B. DAL
    DAL is the stock ticker symbol for Delta Air Lines, a major U.S.-based international airline.
  • C. DCA
    DCA (Defense Communications Agency) was a U.S. Department of Defense organization responsible for managing and overseeing military communications networks, including early internet precursor systems.
  • D. DCA
    DCA is the three-letter IATA airport code for Ronald Reagan Washington National Airport, the primary domestic airport serving Washington, D.C.
  • E. AEX index
    The AEX index is a benchmark stock market index that tracks the performance of the largest and most actively traded companies listed on the Amsterdam Stock Exchange.
  • 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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25ded68c88190b1fc595ce329aeb9 completed Feb. 28, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a39153528c8190a0f1e69a3f94b305 completed March 1, 2026, 1:07 a.m.
NEDg Description generation batch_69a391aa604481909f1b08f7eb9709f4 completed March 1, 2026, 1:08 a.m.
NED2 Entity disambiguation (via description) batch_69a3922dd17c819099bcc68a19f48e10 completed March 1, 2026, 1:11 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.