Triple
T5845769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan Black |
E129705
|
entity |
| Predicate | modeOfAttackSurvived |
P4333
|
FINISHED |
| Object | mass shooting |
—
|
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: mass shooting | Statement: [Alan Black, modeOfAttackSurvived, mass shooting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modeOfAttackSurvived Context triple: [Alan Black, modeOfAttackSurvived, mass shooting]
-
A.
survivesAs
Indicates that one entity continues to exist or persist in place of, or after the end or transformation of, another entity.
-
B.
survivesIn
Indicates that an entity remains alive, functional, or intact within a specified environment, condition, or context.
-
C.
survivingFrom
Indicates that one entity continues to live, exist, or remain after another related entity has ended, disappeared, or ceased to exist.
-
D.
tookHeavyDamageAt
Indicates that an entity experienced severe or substantial damage at a specific location or point in time.
-
E.
attackType
chosen
Indicates the specific method, style, or category of attack used in an aggressive or hostile action between entities.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c0334412388190bc594794ec5754f9 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:55 p.m.