Triple
T11127206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M Bureau |
E263171
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | M |
unclear NED1
|
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: M | Statement: [M Bureau, hasAbbreviation, M]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M Context triple: [M Bureau, hasAbbreviation, M]
-
A.
M
M is a music producer and composer known for creating the soundtrack to the French thriller film "Tell No One."
-
B.
M
M is a functional data mashup and query language used in Microsoft Power BI and related tools for data transformation and preparation.
-
C.
M
M is a New York City Subway service that runs along the IND Sixth Avenue Line in Manhattan and connects Brooklyn and Queens.
-
D.
M
M is an experimental musical composition by avant-garde American composer John Cage, reflecting his innovative approaches to sound and structure.
-
E.
M
M is the standard notation for the Monster group, the largest sporadic simple group in group theory and a central object in the study of finite simple groups and monstrous moonshine.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e82fc5f88190b34c55de3d50f6a7 |
completed | April 9, 2026, 5:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d8b3ce4819082f9efcf8dec4f1a |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 8, 2026, 9:28 p.m.