Triple
T17049494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack's mother |
E413655
|
entity |
| Predicate | reactionToMagicBeans |
P125660
|
FINISHED |
| Object | throws the beans out of the window |
—
|
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: throws the beans out of the window | Statement: [Jack's mother, reactionToMagicBeans, throws the beans out of the window]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reactionToMagicBeans Context triple: [Jack's mother, reactionToMagicBeans, throws the beans out of the window]
-
A.
reactionToProphecy
Indicates how an entity responds or behaves in consequence to a given prophecy.
-
B.
victimOfBeaning
Indicates that one entity is the target or recipient of a beaning (being struck by a thrown object, typically a ball) carried out by another entity.
-
C.
usesMagic
Indicates that an entity performs actions or achieves effects by employing magical powers or supernatural abilities.
-
D.
usesMagicFor
Indicates that one entity employs or applies magic as a means to achieve, affect, or perform something involving another entity or context.
-
E.
protagonistReaction
Indicates how a main character responds emotionally or behaviorally to a particular event, situation, or stimulus.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa092f08190a9e37404a9de662c |
completed | April 18, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:34 a.m.