Triple
T36412771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Memory Charm |
E896924
|
entity |
| Predicate | canBeMisusedFor |
P175308
|
FINISHED |
| Object | covering up crimes |
—
|
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: covering up crimes | Statement: [Memory Charm, canBeMisusedFor, covering up crimes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeMisusedFor Context triple: [Memory Charm, canBeMisusedFor, covering up crimes]
-
A.
canBeExploitedFor
chosen
Indicates that one entity is capable of being used or taken advantage of by another entity to obtain some benefit, resource, or outcome.
-
B.
misuseCanConstitute
Indicates that improper or incorrect use of something can amount to, or be considered as, a particular offense, violation, or condition.
-
C.
riskIfMisused
Indicates that the subject has the potential to cause harm, danger, or negative consequences if it is used improperly or irresponsibly.
-
D.
isExploitedFor
Indicates that one entity is unfairly or abusively used by another entity as a resource, means, or advantage for the latter’s benefit.
-
E.
isOftenMisusedBy
Indicates that something is frequently used incorrectly or inappropriately by a particular entity or group.
- 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_69f76e54ce408190849acc3f7758937c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fee335cb08819097e3a0e09d5ebf49 |
completed | May 9, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69fee2c74fd88190acfc045ab07b7f6b |
completed | May 9, 2026, 7:31 a.m. |
Created at: May 3, 2026, 4:10 p.m.