Triple
T13559924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Reading |
E323878
|
entity |
| Predicate | usesLightEffect |
P69537
|
FINISHED |
| Object | carefully modulated light |
—
|
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: carefully modulated light | Statement: [The Reading, usesLightEffect, carefully modulated light]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLightEffect Context triple: [The Reading, usesLightEffect, carefully modulated light]
-
A.
hasLightingEffect
chosen
Indicates that one entity applies, produces, or is associated with a particular lighting effect on another entity or environment.
-
B.
usesLightingFor
Indicates that one entity employs or relies on a particular lighting setup, technology, or condition to achieve a purpose or perform an action.
-
C.
canLight
Indicates that one entity has the ability or capacity to provide or emit light to another entity or environment.
-
D.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
E.
hasLightShow
Indicates that an entity features or presents a light-based visual display or performance.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae13bec4819084c1770638c00ed9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:47 p.m.