Triple
T17175963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elora Danan |
E416858
|
entity |
| Predicate | threatTypeFaced |
P50110
|
FINISHED |
| Object | attempted ritual sacrifice by Queen Bavmorda |
—
|
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: attempted ritual sacrifice by Queen Bavmorda | Statement: [Elora Danan, threatTypeFaced, attempted ritual sacrifice by Queen Bavmorda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threatTypeFaced Context triple: [Elora Danan, threatTypeFaced, attempted ritual sacrifice by Queen Bavmorda]
-
A.
threatType
chosen
Indicates the specific category or nature of a threat that one entity poses or represents in relation to another.
-
B.
threatTypeEngaged
Indicates that an entity has actively engaged with or responded to a specific type of threat.
-
C.
threatTypeAddressed
Indicates that a given action, measure, or entity is specifically intended to counter or mitigate a particular type of threat.
-
D.
threatCategory
Indicates the classification of a threat according to its type, severity, or nature within a defined risk or security framework.
-
E.
threatContained
Indicates that an identified threat has been successfully neutralized, controlled, or otherwise prevented from causing further harm or escalation.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0cec448190b30466628a2ff23f |
completed | April 18, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e383141ae0819096acd71683637cbc |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:37 a.m.