Triple
T21480866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tammy and the Millionaire |
E529984
|
entity |
| Predicate | storyContinuationOf |
P20918
|
FINISHED |
| Object | earlier Tammy stories |
—
|
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: earlier Tammy stories | Statement: [Tammy and the Millionaire, storyContinuationOf, earlier Tammy stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyContinuationOf Context triple: [Tammy and the Millionaire, storyContinuationOf, earlier Tammy stories]
-
A.
continuedBy
chosen
Indicates that one entity carries on, extends, or resumes the activity, process, or sequence initiated by another entity.
-
B.
storyBy
Indicates that one entity is the creator or author of the story associated with another entity.
-
C.
storyEngine
Indicates that one entity functions as a narrative-generating or plot-controlling mechanism for another entity or set of events.
-
D.
fictionContinuity
Indicates that two or more fictional works share the same narrative continuity, treating events and developments as occurring within a single consistent storyline or universe.
-
E.
storyElement
Indicates that one entity functions as a narrative component or part within the structure of another entity’s story.
- 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_69e0c45acc3881908e38d3f28964152b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea338f988190a3044f8d02a567fe |
completed | April 23, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69e631ec1d048190b6da97da8222e413 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:20 p.m.