Triple
T35043288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lemongrab |
E1011125
|
entity |
| Predicate | relationshipToPrincessBubblegum |
P89053
|
FINISHED |
| Object | creation |
—
|
LITERAL FINISHED |
How this triple was built (2 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: creation | Statement: [Lemongrab, relationshipToPrincessBubblegum, creation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToPrincessBubblegum Context triple: [Lemongrab, relationshipToPrincessBubblegum, creation]
-
A.
relationshipToMegMurry
Indicates the specific type of relationship or connection an entity has to Meg Murry.
-
B.
relationshipToPeppermintPatty
Indicates the specific type of personal or social relationship an entity has with Peppermint Patty.
-
C.
relationshipWithBurtVickerman
Indicates that there exists a specific interpersonal or professional connection between an entity and Burt Vickerman.
-
D.
relationshipToPrincess
chosen
Indicates the specific familial, social, or romantic connection that one entity has to a princess.
-
E.
relationshipToHomer
Indicates the specific familial or social relationship that one entity has to Homer.
- F. None of above.
Provenance (3 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_69f76dcfdda48190b1ebae5da8b54f12 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.