Triple
T8566741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabey |
E202820
|
entity |
| Predicate | storyStructureFunction |
P7328
|
FINISHED |
| Object | drives main plot of On the Town |
—
|
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: drives main plot of On the Town | Statement: [Gabey, storyStructureFunction, drives main plot of On the Town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyStructureFunction Context triple: [Gabey, storyStructureFunction, drives main plot of On the Town]
-
A.
storyFunction
chosen
Indicates that one entity serves a particular narrative role or function within the story structure of another entity.
-
B.
storyElement
Indicates that one entity functions as a narrative component or part within the structure of another entity’s story.
-
C.
storyline
Indicates that one entity serves as the narrative plot or sequence of events associated with another entity.
-
D.
storyBy
Indicates that one entity is the creator or author of the story associated with another entity.
-
E.
textualStructure
Indicates how parts of a text are organized and related to each other within its overall structure.
- 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9d467c08190b2014d71ebbf8bbc |
completed | March 31, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69cbd11856048190a1ce4b83a38f6965 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:20 p.m.