Triple
T1500764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vivian Lake Brady |
E29789
|
entity |
| Predicate | publicAppearanceContext |
P23992
|
FINISHED |
| Object | sports events |
—
|
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: sports events | Statement: [Vivian Lake Brady, publicAppearanceContext, sports events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicAppearanceContext Context triple: [Vivian Lake Brady, publicAppearanceContext, sports events]
-
A.
canonicalContext
Indicates the standard or primary contextual framework within which an entity, statement, or resource is to be interpreted.
-
B.
originContext
Indicates the situational or environmental circumstances from which an entity, event, or piece of information originates.
-
C.
systemContext
Indicates the contextual conditions, settings, or environment within which a system operates or an interaction occurs.
-
D.
appearsAs
Indicates that one entity is presented, perceived, or manifested in the form, role, or guise of another entity.
-
E.
depictionContext
chosen
Indicates the situational or environmental setting in which something is depicted or represented.
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6f2d7f881909188a3e5614335cd |
completed | March 1, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69a4c48a8cf48190a6ebf8d44a608a06 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:12 p.m.