Triple
T14160975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonah E. Kelley |
E350942
|
entity |
| Predicate | actedDespiteWounds |
P113056
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Jonah E. Kelley, actedDespiteWounds, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: actedDespiteWounds Context triple: [Jonah E. Kelley, actedDespiteWounds, yes]
-
A.
wasWoundedIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or conflict.
-
B.
firstWoundInflictedBy
Indicates that the referenced wound is the earliest (chronologically first) injury inflicted by the specified agent on the specified target.
-
C.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
-
D.
damageAssociatedWith
Indicates a relationship where one entity is linked to causing, contributing to, or being responsible for damage affecting another entity.
-
E.
hasApproximateNumberOfWounds
Indicates that an entity has a number of wounds that is known only approximately rather than as an exact count.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61393f308190bb357e2bd1916f94 |
completed | April 14, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69de05b8434c81908c33b1b513463b12 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239a02e881909b0e2679487e4ab2 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 12:59 a.m.