Triple
T10402469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marv Albert |
E245180
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Marv
Marv is a masculine given name, often used as a shortened form of Marvin.
|
E861745
|
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: Marv | Statement: [Marv Albert, givenName, Marv]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marv Context triple: [Marv Albert, givenName, Marv]
-
A.
Marv
Marv is an ancient city in present-day Turkmenistan that was a major Silk Road hub and one of the great cultural and commercial centers of the Islamic world.
-
B.
Marvin
Marvin is the given first name of Pro Football Hall of Fame coach Marv Levy, known for leading the Buffalo Bills to four consecutive Super Bowl appearances.
-
C.
Marvin
Marvin is a given name most famously associated with Marvin Minsky, a pioneering cognitive scientist and co-founder of the field of artificial intelligence.
-
D.
Marvin
Marvin is a character featured in the musical works of American composer and lyricist William Finn, notably in his "Marvin Trilogy" of shows.
-
E.
MARV
MARV is a British film and television production company founded by producer Matthew Vaughn, known for movies such as "Kick-Ass," "Kingsman," and "Layer Cake."
- 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: Marv Triple: [Marv Albert, givenName, Marv]
Generated description
Marv is a masculine given name, often used as a shortened form of Marvin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marv Target entity description: Marv is a masculine given name, often used as a shortened form of Marvin.
-
A.
Marv
Marv is an ancient city in present-day Turkmenistan that was a major Silk Road hub and one of the great cultural and commercial centers of the Islamic world.
-
B.
Marvin
Marvin is the given first name of Pro Football Hall of Fame coach Marv Levy, known for leading the Buffalo Bills to four consecutive Super Bowl appearances.
-
C.
Marvin
Marvin is a given name most famously associated with Marvin Minsky, a pioneering cognitive scientist and co-founder of the field of artificial intelligence.
-
D.
Marvin
Marvin is a character featured in the musical works of American composer and lyricist William Finn, notably in his "Marvin Trilogy" of shows.
-
E.
MARV
MARV is a British film and television production company founded by producer Matthew Vaughn, known for movies such as "Kick-Ass," "Kingsman," and "Layer Cake."
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9e42da08190a5383df3df6d3c18 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fbd13c888190b3a79a9aacb5291e |
completed | April 9, 2026, 7:19 p.m. |
| NEDg | Description generation | batch_69d822d597088190bf3dca85e1ddb890 |
completed | April 9, 2026, 10:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d859cc1aac8190ab232bb4e4e4fac1 |
completed | April 10, 2026, 2 a.m. |
Created at: April 6, 2026, 12:08 p.m.