Triple
T38571161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selina Lo |
E929274
|
entity |
| Predicate | stuntBackground |
P191204
|
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: [Selina Lo, stuntBackground, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stuntBackground Context triple: [Selina Lo, stuntBackground, yes]
-
A.
backgroundsBy
Indicates that something is supported, financed, or endorsed by a particular person, group, or organization in the background.
-
B.
scenesReshotWith
Indicates that certain scenes from a work were filmed again, typically with changes, using the specified other scenes or production instance.
-
C.
politicalBackdropFor
Indicates that one situation, event, or context serves as the political background or setting within which another event or relationship occurs or is interpreted.
-
D.
musicalBackdrop
Indicates that one entity serves as the background music or ambient sound accompanying another entity or event.
-
E.
scenes
Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
- 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_69f76ebd2248819083978362d81fa35e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
| PDg | Predicate description generation | batch_69fcdaa2bfc08190beccabb0f1782d0d |
completed | May 7, 2026, 6:32 p.m. |
Created at: May 3, 2026, 4:32 p.m.