Triple
T19098490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthieu Chedid |
E467467
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
M
M is the stage name of French singer-songwriter and multi-instrumentalist Matthieu Chedid, known for his eclectic pop-rock music and flamboyant performances.
|
E1358254
|
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: M | Statement: [Matthieu Chedid, alsoKnownAs, M]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M Context triple: [Matthieu Chedid, alsoKnownAs, M]
-
A.
M
M is a functional data mashup and query language used in Microsoft Power BI and related tools for data transformation and preparation.
-
B.
M
M is the New York Stock Exchange ticker symbol for Macy's, Inc., a major American department store chain.
-
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 a landmark 1931 German thriller film by Fritz Lang, renowned as an early and influential work in the serial killer and crime genre.
-
E.
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.
- 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: M Triple: [Matthieu Chedid, alsoKnownAs, M]
Generated description
M is the stage name of French singer-songwriter and multi-instrumentalist Matthieu Chedid, known for his eclectic pop-rock music and flamboyant performances.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: M Target entity description: M is the stage name of French singer-songwriter and multi-instrumentalist Matthieu Chedid, known for his eclectic pop-rock music and flamboyant performances.
-
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 nickname or alternate name for Papa M, the musical project of American multi-instrumentalist David Pajo known for its experimental and post-rock-influenced sound.
-
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 introspective zombie protagonist of the novel and film "Warm Bodies," whose gradual recovery of humanity drives the story’s unconventional romantic plot.
-
E.
M
M is the codename for James Bond’s stern and authoritative superior who heads the British Secret Service in the 007 franchise.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36b279c819091a8d51f044bc644 |
completed | April 20, 2026, 8:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05dd9b4e0c8190b235b0d7a068a1e7 |
completed | May 14, 2026, 2:35 p.m. |
| NEDg | Description generation | batch_6a05dfcf14788190a75298641ba20e0e |
completed | May 14, 2026, 2:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05e10ae8188190a9dce95fa838ff7f |
completed | May 14, 2026, 2:49 p.m. |
Created at: April 10, 2026, 12:04 p.m.