Triple
T29327042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officer Zavala |
E743677
|
entity |
| Predicate | onScreenDynamic |
P128578
|
FINISHED |
| Object | banter and camaraderie with Brian Taylor |
—
|
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: banter and camaraderie with Brian Taylor | Statement: [Officer Zavala, onScreenDynamic, banter and camaraderie with Brian Taylor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onScreenDynamic Context triple: [Officer Zavala, onScreenDynamic, banter and camaraderie with Brian Taylor]
-
A.
onScreenDynamicWith
chosen
Indicates that two entities are simultaneously visible and interacting or changing together within the same on-screen context.
-
B.
hasOnScreenDynamic
Indicates that one entity displays or presents another entity as a changing or interactive element on a screen.
-
C.
onScreenStatus
Indicates that an entity’s current presence or visibility state is being specified relative to a screen or display.
-
D.
hasOnScreenRelative
Indicates that one entity has a family member who appears or is depicted on screen in relation to it.
-
E.
hasOnscreenFunction
Indicates that an entity serves a particular role or performs a specific function when it appears on screen.
- 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_69f09125f784819080f4e9fce9fe624f |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6689671f881909a1e1b2bfa20b17e |
completed | May 2, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69f660f2e3708190ab658652bcfc04d0 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 1:27 p.m.