Triple
T13027609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No More Drama |
E326347
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Crazy Games
Crazy Games is a song featured on Mary J. Blige’s album "No More Drama."
|
E1016738
|
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: Crazy Games | Statement: [No More Drama, hasPart, Crazy Games]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crazy Games Context triple: [No More Drama, hasPart, Crazy Games]
-
A.
Ghost Games
Ghost Games is a Swedish video game development studio best known for leading several modern entries in the Need for Speed racing franchise.
-
B.
Fun and Games
"Fun and Games" is the title of the first act of Edward Albee’s play "Who’s Afraid of Virginia Woolf?", in which a seemingly lighthearted evening gradually reveals the toxic dynamics of a middle-aged couple’s marriage.
-
C.
Totally Games
Totally Games was a video game development studio best known for creating the Star Wars: X-Wing and TIE Fighter space combat simulators.
-
D.
The Happy Games
The Happy Games was the official motto of the 1972 Summer Olympics in Munich, reflecting the organizers’ aim to present a cheerful, peaceful image of Germany.
-
E.
The Gamester
The Gamester is a Caroline-era tragicomedy play by English dramatist James Shirley, centered on themes of gambling, honor, and social intrigue.
- 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: Crazy Games Triple: [No More Drama, hasPart, Crazy Games]
Generated description
Crazy Games is a song featured on Mary J. Blige’s album "No More Drama."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Crazy Games Target entity description: Crazy Games is a song featured on Mary J. Blige’s album "No More Drama."
-
A.
Ghost Games
Ghost Games is a Swedish video game development studio best known for leading several modern entries in the Need for Speed racing franchise.
-
B.
Fun and Games
"Fun and Games" is the title of the first act of Edward Albee’s play "Who’s Afraid of Virginia Woolf?", in which a seemingly lighthearted evening gradually reveals the toxic dynamics of a middle-aged couple’s marriage.
-
C.
Totally Games
Totally Games was a video game development studio best known for creating the Star Wars: X-Wing and TIE Fighter space combat simulators.
-
D.
The Happy Games
The Happy Games was the official motto of the 1972 Summer Olympics in Munich, reflecting the organizers’ aim to present a cheerful, peaceful image of Germany.
-
E.
The Gamester
The Gamester is a Caroline-era tragicomedy play by English dramatist James Shirley, centered on themes of gambling, honor, and social intrigue.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97efc07488190a15f3e41ea2db45c |
completed | April 10, 2026, 10:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c12191b08190abf4123995116ebc |
completed | May 3, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_69f6c562d10c8190b76dbf50a0101bae |
completed | May 3, 2026, 3:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6c635fc888190891a79da9d7984a0 |
completed | May 3, 2026, 3:51 a.m. |
Created at: April 9, 2026, 8:53 p.m.