Triple
T23905413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jennie Wade |
E601178
|
entity |
| Predicate | shotThrough |
P154032
|
FINISHED |
| Object | door of the house where she was staying |
—
|
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: door of the house where she was staying | Statement: [Jennie Wade, shotThrough, door of the house where she was staying]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shotThrough Context triple: [Jennie Wade, shotThrough, door of the house where she was staying]
-
A.
shotBy
Indicates that one entity fired a projectile or weapon that hit and wounded or killed another entity.
-
B.
shotOn
Indicates that one entity fired or took a shot at another entity, typically in a sports or combat context.
-
C.
shotFrom
Indicates that something is propelled or discharged starting at a particular source or origin.
-
D.
shoots
Indicates that one entity propels a projectile or discharge toward another entity, typically with the intent to hit or affect it.
-
E.
shotDuring
Indicates that one event or action of shooting occurred within the temporal span of another specified event or time period.
- 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_69e295364a488190bcac702e9bb7f764 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cde13e88819086bbd0bc4a5b6a36 |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f167dca3608190ace9d2eef56b2af6 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 8:30 p.m.