Triple
T3132418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VH1 |
E65444
|
entity |
| Predicate | laterFocusedOn |
P37801
|
FINISHED |
| Object | reality television 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: reality television series | Statement: [VH1, laterFocusedOn, reality television series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterFocusedOn Context triple: [VH1, laterFocusedOn, reality television series]
-
A.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
focusAfterTransition
chosen
Indicates that focus is moved to a specific element or area after a transition or state change has completed.
-
C.
formerFocus
Indicates that an entity previously served as the primary focus or main subject of attention, but no longer holds that status.
-
D.
focusesBy
Indicates that one entity directs its attention, effort, or emphasis toward another entity or specific aspect of it.
-
E.
mayProvideFocus
Indicates that one entity can potentially direct attention, emphasis, or concentration toward another entity or aspect.
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada55f77b881908866fc43bdb18185 |
completed | March 8, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69ad9df62e548190b053e1478deed467 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:04 p.m.