Triple
T13644539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alien Swirling Saucers |
E326067
|
entity |
| Predicate | featuresLightingEffects |
P69537
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Alien Swirling Saucers, featuresLightingEffects, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresLightingEffects Context triple: [Alien Swirling Saucers, featuresLightingEffects, yes]
-
A.
hasLightingEffect
chosen
Indicates that one entity applies, produces, or is associated with a particular lighting effect on another entity or environment.
-
B.
featuresLightingBy
Indicates that something includes or showcases lighting created, provided, or designed by a specified entity.
-
C.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
D.
lightOrganFunction
Indicates that one entity serves as the functional light-producing organ or structure for another entity.
-
E.
lightingCharacteristic
Indicates the specific qualities or properties of how something is lit, such as brightness, color, direction, or style of illumination.
- 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_69d8076beddc8190a53156f5bea77f5e |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc60635d08190899806fe8936f02a |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8a027081908d8f884b89707a5e |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:51 p.m.