Triple
T16007336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Austen |
E388251
|
entity |
| Predicate | hasFlashSidewaysEpisodes |
P120744
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Kate Austen, hasFlashSidewaysEpisodes, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlashSidewaysEpisodes Context triple: [Kate Austen, hasFlashSidewaysEpisodes, yes]
-
A.
hasEpisodes
Indicates that one entity (typically a series or show) contains or is composed of multiple episode entities.
-
B.
hasBlackAndWhiteEpisodes
Indicates that the subject includes or features episodes presented in black and white.
-
C.
hasSpinOff
Indicates that one entity is a derivative or spin-off product, work, or organization that originated from another entity.
-
D.
hasEpisode
Indicates that something, typically a series or program, includes a specific episode as one of its constituent parts.
-
E.
hasFictionalShowWithinShow
Indicates that one show contains or features another fictional show within its narrative.
- F. None of above. chosen
Provenance (4 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142dc081c819082527e3fa8773460 |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e173af801c8190bfc0f602831bb594 |
completed | April 16, 2026, 11:41 p.m. |
Created at: April 10, 2026, 4:55 a.m.