Triple
T13558977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arliss |
E323853
|
entity |
| Predicate | featuresCameosFrom |
P90355
|
FINISHED |
| Object | professional athletes |
—
|
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: professional athletes | Statement: [Arliss, featuresCameosFrom, professional athletes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCameosFrom Context triple: [Arliss, featuresCameosFrom, professional athletes]
-
A.
cameoCharacter
Indicates that one entity appears briefly or in a minor, special-guest role within the context or work associated with another entity.
-
B.
featuresPerformerCameo
chosen
Indicates that the subject includes a brief, special appearance by a performer who is not part of the main cast or lineup.
-
C.
featuresCast
Indicates that a creative work includes a particular person or group as part of its cast.
-
D.
hasDirectorCameo
Indicates that the director of a work appears in a cameo role within that same work.
-
E.
laterFeaturedCastFrom
Indicates that one entity appears as a featured cast member in a later work, episode, or installment relative to 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae13bec4819084c1770638c00ed9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:47 p.m.