Triple
T20983374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kindred |
E516824
|
entity |
| Predicate | conditionalEffect |
P142355
|
FINISHED |
| Object | Can reveal the killer’s aura under certain conditions |
—
|
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: Can reveal the killer’s aura under certain conditions | Statement: [Kindred, conditionalEffect, Can reveal the killer’s aura under certain conditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conditionalEffect Context triple: [Kindred, conditionalEffect, Can reveal the killer’s aura under certain conditions]
-
A.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
-
B.
tookEffect
Indicates that a change, rule, condition, or event became active, operative, or started producing its intended consequences.
-
C.
predictedEffect
Indicates that one entity is expected to cause, influence, or result in a particular outcome or consequence for another entity.
-
D.
providesEffect
Indicates that one entity causes, delivers, or produces a particular effect or outcome on another entity.
-
E.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
- 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_69e0b4ffac148190bbade9f0eceb660b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fbe03244819097630333e70c4e88 |
completed | April 21, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69e5dbe6976081908abd4e9c8734bae9 |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2df1a888190b5b478e76bdf7fdf |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 1:48 p.m.