Triple
T9473932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Light (Next to Normal) |
E228462
|
entity |
| Predicate | recurringImage |
P41815
|
FINISHED |
| Object | light in the darkness |
—
|
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: light in the darkness | Statement: [Light (Next to Normal), recurringImage, light in the darkness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringImage Context triple: [Light (Next to Normal), recurringImage, light in the darkness]
-
A.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
B.
publicImage
Indicates how an entity is perceived or represented by the general public or broader audience.
-
C.
evokesImageOf
chosen
Indicates that one entity triggers or brings to mind a mental image or visual representation of another entity.
-
D.
recurringSegmentOn
Indicates that one entity appears repeatedly as a regular segment or feature within another entity, such as a show, publication, or series.
-
E.
imagedIn
Indicates that one entity appears within or is depicted in an image associated with another entity.
- 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_69ca847162c48190b079076c9595513c |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ff23aec8190b5341eb9bd816a43 |
completed | April 1, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69cca55f01b081908dc0f12eaa45f832 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:54 p.m.