Triple
T20149930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EC Comics |
E491408
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object |
MAD
MAD is a long-running American humor magazine famous for its satirical takes on popular culture, politics, and everyday life.
|
E1415181
|
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: MAD | Statement: [EC Comics, knownFor, MAD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MAD Context triple: [EC Comics, knownFor, MAD]
-
A.
MAD
MAD is the three-letter IATA airport code for Adolfo Suárez Madrid–Barajas Airport, the main international airport serving Madrid, Spain.
-
B.
MAD
MAD is a museum dedicated to contemporary art and design, showcasing innovative and experimental works across various media.
-
C.
M.A.D.
M.A.D. is the nefarious criminal organization led by the villain Dr. Claw in the animated series "Inspector Gadget."
-
D.
U Mad
"U Mad" is a hip-hop single by American rapper Vic Mensa featuring Kanye West, known for its aggressive energy and confrontational lyrics.
-
E.
MDA
MDA (Monochrome Display Adapter) is IBM's original text-only video display standard for early IBM PCs, providing high-resolution monochrome output without graphics capabilities.
- 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: MAD Triple: [EC Comics, knownFor, MAD]
Generated description
MAD is a long-running American humor magazine famous for its satirical takes on popular culture, politics, and everyday life.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MAD Target entity description: MAD is a long-running American humor magazine famous for its satirical takes on popular culture, politics, and everyday life.
-
A.
MAD
MAD is the three-letter IATA airport code for Adolfo Suárez Madrid–Barajas Airport, the main international airport serving Madrid, Spain.
-
B.
MAD
MAD is a museum dedicated to contemporary art and design, showcasing innovative and experimental works across various media.
-
C.
M.A.D.
M.A.D. is the nefarious criminal organization led by the villain Dr. Claw in the animated series "Inspector Gadget."
-
D.
U Mad
"U Mad" is a hip-hop single by American rapper Vic Mensa featuring Kanye West, known for its aggressive energy and confrontational lyrics.
-
E.
MDA
MDA (Monochrome Display Adapter) is IBM's original text-only video display standard for early IBM PCs, providing high-resolution monochrome output without graphics capabilities.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667a1c5848190975b17ab07251f8b |
completed | April 20, 2026, 5:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08346f7b708190b006704558b25a67 |
completed | May 16, 2026, 9:10 a.m. |
| NEDg | Description generation | batch_6a08357acba08190be9fcedf1ea0f19d |
completed | May 16, 2026, 9:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0836a5cfdc81908806d83acd257acd |
completed | May 16, 2026, 9:19 a.m. |
Created at: April 11, 2026, 11:33 p.m.