Triple
T13601965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MDCT |
E324964
|
entity |
| Predicate | usedInStandard |
P1587
|
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: [MDCT, usedInStandard, WMA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WMA Context triple: [MDCT, usedInStandard, 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb07ad3f48190a2173e42c5cfedb1 |
completed | April 12, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f92224c8190b66adef1291cd47f |
completed | May 3, 2026, 5:02 p.m. |
Created at: April 9, 2026, 9:49 p.m.