Triple
T8320105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "Here’s Johnny!" scene |
E194807
|
entity |
| Predicate | threatensWithWeapon |
P22414
|
FINISHED |
| Object | axe |
—
|
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: axe | Statement: ["Here’s Johnny!" scene, threatensWithWeapon, axe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threatensWithWeapon Context triple: ["Here’s Johnny!" scene, threatensWithWeapon, axe]
-
A.
threatenedToKill
Indicates that one entity has made a threat or expressed an intention to kill another entity.
-
B.
threatToHumans
Indicates that the subject poses or represents a potential danger, harm, or risk to humans.
-
C.
threat
Indicates a relationship where one entity expresses or poses potential harm, danger, or negative consequences toward another entity.
-
D.
weaponUsedAgainst
chosen
Indicates that a particular weapon or instrument is employed in an act of aggression, attack, or harm directed toward a specific target or entity.
-
E.
threatTypeEngaged
Indicates that an entity has actively engaged with or responded to a specific type of threat.
- 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_69ca82e7a8a88190a32bb5cc0feb012d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f6686a0819094abc2bfd2e500a5 |
completed | March 31, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69cb70bf689c8190a9d9b6b872abf53d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:55 p.m.