Triple
T25868218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kathy Griffin |
E651677
|
entity |
| Predicate | grammyAwardFor |
P50860
|
FINISHED |
| Object |
Kathy Griffin: Calm Down Gurrl
"Kathy Griffin: Calm Down Gurrl" is a comedy album and stand-up special by comedian Kathy Griffin, showcasing her sharp, celebrity-focused observational humor.
|
E1710708
|
NE FINISHED |
How this triple was built (3 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: Kathy Griffin: Calm Down Gurrl | Statement: [Kathy Griffin, grammyAwardFor, Kathy Griffin: Calm Down Gurrl]
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: Kathy Griffin: Calm Down Gurrl Triple: [Kathy Griffin, grammyAwardFor, Kathy Griffin: Calm Down Gurrl]
Generated description
"Kathy Griffin: Calm Down Gurrl" is a comedy album and stand-up special by comedian Kathy Griffin, showcasing her sharp, celebrity-focused observational humor.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grammyAwardFor Context triple: [Kathy Griffin, grammyAwardFor, Kathy Griffin: Calm Down Gurrl]
-
A.
grammyWins
Indicates that an entity has received one or more Grammy Awards as a winner.
-
B.
grammyNomination
chosen
Indicates that an entity has been officially nominated for a Grammy Award in a particular category and year.
-
C.
albumAwardedTo
Indicates that a particular album has been granted or assigned to a specific recipient, such as an artist or group.
-
D.
emmyAwardFor
Indicates that an entity has received or is associated with a specific Emmy Award for a particular work or achievement.
-
E.
yearOfGrammyWins
Indicates the specific year or years in which an entity received one or more Grammy Awards.
- F. None of above.
Provenance (6 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_69e7ab3a199c81909227cb964cacfe24 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f602da6e808190a3ff3786b1b07c65 |
completed | May 2, 2026, 1:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a11272ef1808190bd8185a1f1b79d5c |
completed | May 23, 2026, 4:03 a.m. |
| NEDg | Description generation | batch_6a1134afc1c88190a1c0bf52f223399e |
completed | May 23, 2026, 5:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1135f6bbcc819090e8ec142966d305 |
completed | May 23, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69f4939148dc81908706cec7d85291bc |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 8:07 a.m.