Triple
T9385248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howea forsteriana |
E225888
|
entity |
| Predicate | lightPreferenceIndoors |
P60432
|
FINISHED |
| Object | low to medium 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: low to medium light | Statement: [Howea forsteriana, lightPreferenceIndoors, low to medium light]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightPreferenceIndoors Context triple: [Howea forsteriana, lightPreferenceIndoors, low to medium light]
-
A.
lightType
Indicates the specific category or kind of light associated with an entity or lighting setup.
-
B.
lightRange
Indicates the distance or area over which a light source effectively emits or illuminates.
-
C.
preferredLight
chosen
Indicates that one entity favors or is best suited to a particular lighting condition or level of illumination.
-
D.
illuminationCondition
Indicates the lighting or brightness conditions under which an event, observation, or interaction takes place.
-
E.
lightLevel
Indicates the intensity or amount of light present in a given context or environment.
- 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50d142008190840e131e8f1940f9 |
completed | April 1, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69cca53bd6ec81909bf403ce304e5c08 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:44 p.m.