Triple
T357210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sirena Deep |
E7569
|
entity |
| Predicate | lightLevel |
P12262
|
FINISHED |
| Object | complete darkness at depth |
—
|
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: complete darkness at depth | Statement: [Sirena Deep, lightLevel, complete darkness at depth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightLevel Context triple: [Sirena Deep, lightLevel, complete darkness at depth]
-
A.
lightSourceFor
Indicates that one entity serves as the source of illumination for another entity.
-
B.
lightPath
Indicates the route or trajectory that light follows as it travels between entities or through a medium.
-
C.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
D.
designLuminosity
Indicates the specified luminosity level or brightness characteristics that something is designed or intended to have.
-
E.
led
Indicates that one entity guided, directed, or was in charge of another entity or activity, typically over a period of time.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebaf0c9881909313f98818e7fa58 |
completed | Feb. 28, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69a2e959ce948190a201c017eecb7c95 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea2c44408190946267525c88e811 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.