Triple
T7207543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | École Polytechnique massacre |
E148704
|
entity |
| Predicate | victimDemographic |
P699
|
FINISHED |
| Object | female engineering students |
—
|
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: female engineering students | Statement: [École Polytechnique massacre, victimDemographic, female engineering students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimDemographic Context triple: [École Polytechnique massacre, victimDemographic, female engineering students]
-
A.
victimGroup
chosen
Indicates that one group or entity is the target or recipient of harm, abuse, or wrongdoing caused by another.
-
B.
victimAge
Indicates the age of the person who is the victim in the described event or situation.
-
C.
victimRole
Indicates that one entity participates in an event or situation specifically in the role of the victim or harmed party.
-
D.
victimStatus
Indicates the condition or state of a person who has been harmed or wronged as a result of an event, action, or offense.
-
E.
victimState
Indicates the condition or status that a victim is in as a result of an event, action, or harmful incident.
- 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_69c687e8cf188190b5f3ecffd681f04e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e969c5fc819096bc03bfba12d0cf |
completed | March 27, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69c6e757fed4819091b0a096e3befc3a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:52 p.m.