Triple
T34103465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beneke Fabricators |
E874636
|
entity |
| Predicate | involvedInStorylineWith |
P74692
|
FINISHED |
| Object | Skyler White |
—
|
NE NERFINISHED |
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: Skyler White | Statement: [Beneke Fabricators, involvedInStorylineWith, Skyler White]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvedInStorylineWith Context triple: [Beneke Fabricators, involvedInStorylineWith, Skyler White]
-
A.
involvedActor
Indicates that an entity participates as an actor or participant in the referenced event, activity, or situation.
-
B.
knownForStorylinesAbout
Indicates that an entity is recognized or notable for creating, featuring, or being associated with particular storylines or narrative themes.
-
C.
has part in role
Indicates that an entity participates as a component or constituent specifically in a defined role within a larger whole or process.
-
D.
hasBeenInvolvedIn
chosen
Indicates that an entity has participated in, taken part in, or been connected to a particular event, activity, or situation.
-
E.
knownForStoryline
Indicates that an entity is recognized or notable specifically for its narrative or storyline.
- 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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
Created at: May 1, 2026, 1:53 a.m.