Triple
T26387014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryder rental truck |
E663307
|
entity |
| Predicate | attackInjuriesApproximate |
P25887
|
FINISHED |
| Object | hundreds injured |
—
|
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: hundreds injured | Statement: [Ryder rental truck, attackInjuriesApproximate, hundreds injured]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attackInjuriesApproximate Context triple: [Ryder rental truck, attackInjuriesApproximate, hundreds injured]
-
A.
injuriesApprox
chosen
Indicates an approximate or estimated number or extent of injuries associated with an event or entity.
-
B.
injuryType
Indicates the specific kind or category of injury associated with an entity or event.
-
C.
hasApproximateNumberOfWounds
Indicates that an entity has a number of wounds that is known only approximately rather than as an exact count.
-
D.
injuredIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or action.
-
E.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
- 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_69ee88374adc81909868f3bab374a32f |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f610bc2b288190ae10e6c27e5df786 |
completed | May 2, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f60b89cc048190a9feb24466006be0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 26, 2026, 11:23 p.m.