Triple
T30053505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ken Norton vs. George Foreman |
E763662
|
entity |
| Predicate | impactOnForeman |
P178814
|
FINISHED |
| Object | reinforced image as a devastating puncher |
—
|
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: reinforced image as a devastating puncher | Statement: [Ken Norton vs. George Foreman, impactOnForeman, reinforced image as a devastating puncher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnForeman Context triple: [Ken Norton vs. George Foreman, impactOnForeman, reinforced image as a devastating puncher]
-
A.
impactOnLeader
Indicates that one entity has an effect, influence, or consequence on a leader within a given context.
-
B.
impactOnDirector
Indicates that one entity has an effect, influence, or consequence on a director in the context of a given situation or action.
-
C.
impactOnField
Indicates the effect or influence that one entity, action, or development has on a particular field or domain.
-
D.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
E.
impactStatus
Indicates the current state or condition of how something has affected or influenced a target.
- F. None of above. chosen
Provenance (4 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_69f224716378819087a722e487832b70 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f71421e8d08190807ccfb15d0f0ddb |
completed | May 3, 2026, 9:23 a.m. |
Created at: April 29, 2026, 6:56 p.m.