Triple
T24070507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Howard |
E596211
|
entity |
| Predicate | imageImpact |
P121409
|
FINISHED |
| Object | sensationalized capital punishment in the press |
—
|
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: sensationalized capital punishment in the press | Statement: [Tom Howard, imageImpact, sensationalized capital punishment in the press]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageImpact Context triple: [Tom Howard, imageImpact, sensationalized capital punishment in the press]
-
A.
imageOf
Indicates that one entity is a visual representation or depiction of another entity.
-
B.
chartImpact
Indicates how one factor or action influences the shape, position, or behavior of a chart or graphical representation.
-
C.
hasVisualImpact
chosen
Indicates that one entity affects or influences the visual appearance or aesthetic perception of another.
-
D.
encodingImpact
Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
-
E.
impactOnMeta
Indicates the effect or influence that one entity, action, or condition has on Meta as an outcome or consequence.
- 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_69e288c25c008190850cf447940ab181 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1db17c99881909f97e858fb183d86 |
completed | April 29, 2026, 10:19 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:41 p.m.