Triple
T26497851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leon Errol |
E669330
|
entity |
| Predicate | starredInSeries |
P97661
|
FINISHED |
| Object | Leon Errol two-reel comedy series |
—
|
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: Leon Errol two-reel comedy series | Statement: [Leon Errol, starredInSeries, Leon Errol two-reel comedy series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: starredInSeries Context triple: [Leon Errol, starredInSeries, Leon Errol two-reel comedy series]
-
A.
starOccupationInSeries
Indicates that an individual has a specific occupation or role as a starring character within a particular series.
-
B.
playedInTVSeries
Indicates that an entity (typically a person or character) performed or appeared as part of the cast in a particular television series.
-
C.
seriesStar
chosen
Indicates that an entity serves as a principal performer or featured actor in a series.
-
D.
starredActor
Indicates that an actor performed a leading or significant role in a particular production or work.
-
E.
appearsInSeriesBy
Indicates that one entity (such as a work or character) is featured within a series that is created, authored, or produced by another entity.
- 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_69eeb319007081909642b414b114b35a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6383625cc8190aa223d8ef655743c |
completed | May 2, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69f63709e4848190b5cf322e06b23fb6 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 1:10 a.m.