Triple
T26920143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bill Marks |
E677621
|
entity |
| Predicate | threatInvolves |
P50110
|
FINISHED |
| Object | killing a passenger every 20 minutes |
—
|
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: killing a passenger every 20 minutes | Statement: [Bill Marks, threatInvolves, killing a passenger every 20 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threatInvolves Context triple: [Bill Marks, threatInvolves, killing a passenger every 20 minutes]
-
A.
threatContained
Indicates that an identified threat has been successfully neutralized, controlled, or otherwise prevented from causing further harm or escalation.
-
B.
threatType
chosen
Indicates the specific category or nature of a threat that one entity poses or represents in relation to another.
-
C.
threatInStory
Indicates that one entity poses or represents a danger, menace, or harmful intent toward another entity within the context of a narrative or story.
-
D.
threatTypeEngaged
Indicates that an entity has actively engaged with or responded to a specific type of threat.
-
E.
threatToHumans
Indicates that the subject poses or represents a potential danger, harm, or risk to humans.
- 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_69eee9bdebc48190ba90a12a63e09c73 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f6247480cc8190a887eedaeb94615c |
completed | May 2, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69f623a7539c8190b71797f583da9f63 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 6:06 a.m.