Triple
T21990890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Athleap |
E543082
|
entity |
| Predicate | associatedWithStoryArc |
P39504
|
FINISHED |
| Object | Jim Halpert career change |
—
|
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: Jim Halpert career change | Statement: [Athleap, associatedWithStoryArc, Jim Halpert career change]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithStoryArc Context triple: [Athleap, associatedWithStoryArc, Jim Halpert career change]
-
A.
associatedWithPersonInStory
Indicates that one entity has a connection or involvement with a specific person within the context of a story.
-
B.
associatedTale
Indicates that one entity is linked or connected to a particular tale, story, or narrative.
-
C.
notableStoryArc
chosen
Indicates that there exists a significant or prominent narrative storyline or plot development involving the subject.
-
D.
associatedWithFictionalEvent
Indicates that an entity has a connection or involvement with a fictional event, such as being based on, inspired by, or participating in that imagined occurrence.
-
E.
associatedWithCharacterRole
Indicates that one entity has a connection or linkage to a specific character role played or held by another entity.
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1270d7cbc819086eea86be04a2ec0 |
completed | April 28, 2026, 9:30 p.m. |
| PD | Predicate disambiguation | batch_69e6f6154e408190acc5b2c278acaff4 |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:05 p.m.