Triple
T27782239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dave McFly |
E699363
|
entity |
| Predicate | occupationInOriginalTimeline |
P69186
|
FINISHED |
| Object | fast food worker |
—
|
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: fast food worker | Statement: [Dave McFly, occupationInOriginalTimeline, fast food worker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationInOriginalTimeline Context triple: [Dave McFly, occupationInOriginalTimeline, fast food worker]
-
A.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
B.
hasOccupationDuringStory
chosen
Indicates that an entity holds or performs a particular occupation or job role during the time span covered by the story.
-
C.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
-
D.
laterOccupationApproxDate
Indicates an approximate date or time period when a subject began a subsequent occupation or role after an earlier one.
-
E.
workedPrimarilyIn
Indicates that an entity carried out the majority of its work, activity, or career within a particular field, location, or context.
- 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_69ef6a4b5a9081909c9111396c2be3d2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6617ba4a88190bfc5c305acb4f93f |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 27, 2026, 5:11 p.m.