Triple
T5338681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ploutonion |
E123887
|
entity |
| Predicate | perceivedEffect |
P53074
|
FINISHED |
| Object | dangerous to enter |
—
|
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: dangerous to enter | Statement: [Ploutonion, perceivedEffect, dangerous to enter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: perceivedEffect Context triple: [Ploutonion, perceivedEffect, dangerous to enter]
-
A.
influencedPerceptionOf
Indicates that one entity has affected, shaped, or altered how another entity is perceived or understood.
-
B.
eventEffect
chosen
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
C.
primaryEffect
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
D.
tookEffect
Indicates that a change, rule, condition, or event became active, operative, or started producing its intended consequences.
-
E.
effectOnOthers
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
- 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_69bd464b07f8819095aa76577c9829e4 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85e86edc81908d87933db6489f91 |
completed | March 20, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69bd845a62b081909782863865b257a9 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2 p.m.