Triple
T32174178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scroll of the Ultimate |
E821790
|
entity |
| Predicate | riskIfMisused |
P173283
|
FINISHED |
| Object | catastrophic consequences |
—
|
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: catastrophic consequences | Statement: [Scroll of the Ultimate, riskIfMisused, catastrophic consequences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskIfMisused Context triple: [Scroll of the Ultimate, riskIfMisused, catastrophic consequences]
-
A.
riskIfIgnored
Indicates that a potential negative consequence or danger will likely occur if the associated condition, issue, or action is not addressed or is disregarded.
-
B.
riskIfFailure
Indicates that one entity faces potential negative consequences or harm if another entity fails or an attempted action is unsuccessful.
-
C.
riskIfTooHigh
Indicates that a certain level or value becomes risky or dangerous when it exceeds a specified threshold.
-
D.
riskIfNoncompliance
Indicates that a risk or negative consequence will occur if the specified rules, requirements, or obligations are not complied with.
-
E.
misuseCanConstitute
Indicates that improper or incorrect use of something can amount to, or be considered as, a particular offense, violation, or condition.
- F. None of above. chosen
Provenance (4 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_69f3490699a48190bbef96b198e8fade |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6ba786b188190a59d6b96caa92213 |
completed | May 3, 2026, 3:01 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
| PDg | Predicate description generation | batch_69f6b42902a081909126c7322858a2b3 |
completed | May 3, 2026, 2:34 a.m. |
Created at: May 1, 2026, 12:34 a.m.