Triple

T9740618
Position Surface form Disambiguated ID Type / Status
Subject Advanced Audio Coding E236174 entity
Predicate competesWith P1375 FINISHED
Object WMA E697243 NE FINISHED

How this triple was built (2 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: WMA | Statement: [Advanced Audio Coding, competesWith, WMA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WMA
Context triple: [Advanced Audio Coding, competesWith, WMA]
  • A. WMA chosen
    WMA is a proprietary audio compression format developed by Microsoft as part of its Windows Media framework.
  • B. WMP
    WMP is an abbreviation for Western Malayo-Polynesian, a traditional subgrouping of the Austronesian language family encompassing many languages of western Island Southeast Asia and nearby regions.
  • C. WMV
    WMV (Windows Media Video) is a series of Microsoft-developed video compression formats commonly used for streaming and storing digital video on Windows platforms.
  • D. WAV
    WAV is the vehicle registration code used to identify motor vehicles registered in the municipality of Wavre in Belgium.
  • E. WAV
    WAV is an uncompressed audio file format developed by Microsoft and IBM, commonly used for high-quality sound storage and editing on Windows systems.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca84d3e24481908a476e2231123cf9 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f29a5bc8190b2b391017405c71e completed April 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1afe974608190874e2aba2189de80 completed April 5, 2026, 12:42 a.m.
Created at: March 30, 2026, 8:22 p.m.