Triple
T23537821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ned |
E577650
|
entity |
| Predicate | touchEffect |
P113927
|
FINISHED |
| Object | first touch revives the dead |
—
|
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: first touch revives the dead | Statement: [Ned, touchEffect, first touch revives the dead]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: touchEffect Context triple: [Ned, touchEffect, first touch revives the dead]
-
A.
snapbackEffect
Indicates a relationship where an initial change or intervention triggers a temporary shift that eventually reverses or rebounds back toward the original state, often with unintended or amplified consequences.
-
B.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
C.
touchesState
chosen
Indicates that one entity is in physical contact with, or directly affects, the state or condition of another entity.
-
D.
projectionEffect
Indicates the visual or spatial transformation produced when something is projected from one surface, medium, or viewpoint onto another.
-
E.
arrowEffect
Indicates that one entity causes or produces a directional influence or outcome on another, similar to an arrow showing the effect from source to target.
- 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_69e245f9d5d08190a4a20004e1784e20 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ae1831688190ac06b84729bce160 |
completed | April 29, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:10 p.m.