Triple
T23248740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wally Badarou |
E581661
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | M |
—
|
NE NERFINISHED |
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: [Wally Badarou, associatedAct, M]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M Context triple: [Wally Badarou, associatedAct, M]
-
A.
M
M is a light rail line in San Francisco’s Muni Metro system that runs between the Embarcadero and the southwestern neighborhoods of the city.
-
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 an experimental musical composition by avant-garde American composer John Cage, reflecting his innovative approaches to sound and structure.
-
D.
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.
-
E.
M
chosen
M is a music producer and composer known for creating the soundtrack to the French thriller film "Tell No One."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f4d7e4819085eec6279696db34 |
completed | April 29, 2026, 5:15 a.m. |
Created at: April 17, 2026, 4:10 p.m.