Triple
T34957634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Extreme Risk |
E1008161
|
entity |
| Predicate | characterAffectedByEvent |
P40524
|
FINISHED |
| Object | B'Elanna Torres |
—
|
NE NERFINISHED |
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: B'Elanna Torres | Statement: [Extreme Risk, characterAffectedByEvent, B'Elanna Torres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterAffectedByEvent Context triple: [Extreme Risk, characterAffectedByEvent, B'Elanna Torres]
-
A.
associatedCharacterEvent
Indicates that a character is linked or connected to a particular event in some relevant way.
-
B.
affectedPerson
chosen
Indicates that a particular person is impacted or influenced by an event, action, or condition.
-
C.
eventInfluencedBy
Indicates that an event occurs or unfolds in a way that is causally or significantly affected by another entity, factor, or prior event.
-
D.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
E.
characterizedEventsAs
Indicates that one entity has described, labeled, or interpreted certain events as having particular characteristics or qualities.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff7eb7189c81909a8f73fbc4c48e02 |
completed | May 9, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69ff7e54e11081908fb5ce10c5aa7b53 |
completed | May 9, 2026, 6:35 p.m. |
Created at: May 3, 2026, 4 p.m.