Triple
T17477237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ricinulei |
E425570
|
entity |
| Predicate | sensitivityToLight |
P127606
|
FINISHED |
| Object | adapted to low-light environments |
—
|
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: adapted to low-light environments | Statement: [Ricinulei, sensitivityToLight, adapted to low-light environments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sensitivityToLight Context triple: [Ricinulei, sensitivityToLight, adapted to low-light environments]
-
A.
canLight
Indicates that one entity has the ability or capacity to provide or emit light to another entity or environment.
-
B.
surfaceBrightnessClass
Indicates the qualitative classification of how bright an extended object (such as a galaxy) appears per unit area on the sky.
-
C.
illuminationCondition
Indicates the lighting or brightness conditions under which an event, observation, or interaction takes place.
-
D.
luminescenceCapability
Indicates the ability of an entity to emit light through luminescence.
-
E.
intrinsicBrightness
Indicates the inherent level of light or luminosity an entity possesses, independent of external factors or observation conditions.
- 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451bc3f908190b2c7a2d1f75a43f2 |
completed | April 19, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f341c88190adabe526d8903b05 |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb37d148190b7f38599c06594ee |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:47 a.m.