Triple
T35773656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dylan Klebold |
E1034231
|
entity |
| Predicate | mentalHealthDiscussion |
P109970
|
FINISHED |
| Object | subject of posthumous discussions about depression |
—
|
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: subject of posthumous discussions about depression | Statement: [Dylan Klebold, mentalHealthDiscussion, subject of posthumous discussions about depression]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mentalHealthDiscussion Context triple: [Dylan Klebold, mentalHealthDiscussion, subject of posthumous discussions about depression]
-
A.
discussionPublic
Indicates that a discussion is accessible to the general public rather than being restricted or private.
-
B.
causeOfMentalHealthIssues
Indicates that one entity is a contributing factor in producing or worsening another entity’s mental health issues.
-
C.
canDiscuss
Indicates that one entity is able or permitted to engage in a discussion or conversation with another entity.
-
D.
discussed
Indicates that one entity talked about, examined, or debated a topic, issue, or other entity with someone else.
-
E.
healthTheme
chosen
Indicates that the subject is associated with, focuses on, or is characterized by a particular health-related topic or theme.
- 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_69f76e14a1e081908eddd57bd6fdb3be |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a1f927d08190bd236e0afb3d2bcb |
completed | May 3, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:06 p.m.