Triple
T5741554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim Halpert |
E126624
|
entity |
| Predicate | notablePrank |
P61064
|
FINISHED |
| Object | putting Dwight’s stapler in Jell-O |
—
|
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: putting Dwight’s stapler in Jell-O | Statement: [Jim Halpert, notablePrank, putting Dwight’s stapler in Jell-O]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notablePrank Context triple: [Jim Halpert, notablePrank, putting Dwight’s stapler in Jell-O]
-
A.
notableGag
Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
-
B.
Prank Encounters
chosen
Indicates a relationship where one party orchestrates a deceptive or surprising prank scenario that another party unexpectedly experiences or becomes the target of.
-
C.
notableTheft
Indicates that an entity is involved in a theft event that is widely recognized or significant in some notable way.
-
D.
notableGaffe
Indicates that an entity is known for having made a significant mistake, blunder, or embarrassing error.
-
E.
notableFact
Indicates that there exists a particularly significant or noteworthy fact or piece of information associated with the subject.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b52663c8190ab44258468d4296d |
completed | March 22, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c021ca61688190875bd6107161c284 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:48 p.m.