Triple
T22691903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. tobacco industry |
E561070
|
entity |
| Predicate | facesTrend |
P39078
|
FINISHED |
| Object | declining cigarette consumption in the United States |
—
|
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: declining cigarette consumption in the United States | Statement: [U.S. tobacco industry, facesTrend, declining cigarette consumption in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facesTrend Context triple: [U.S. tobacco industry, facesTrend, declining cigarette consumption in the United States]
-
A.
trends
chosen
Indicates that one entity exhibits a general direction of change or development over time in relation to another reference or context.
-
B.
faceType
Indicates the specific shape or structural category of a face that an entity possesses or is characterized by.
-
C.
followsFace
Indicates that one entity adjusts its position or orientation to continuously track and remain aligned with another entity’s face.
-
D.
socialMediaTrend
Indicates that something is currently popular, widely discussed, or rapidly spreading in visibility and engagement on social media platforms.
-
E.
faceDominatesComposition
Indicates that a face is the primary visual element, controlling the viewer’s attention and overall balance of the composition.
- 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1789adcc48190b4a717166d5dba19 |
completed | April 29, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:13 p.m.