Triple
T5333269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dyson tree |
E123361
|
entity |
| Predicate | atmosphereGenerationMethod |
P62882
|
FINISHED |
| Object | photosynthesis |
—
|
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: photosynthesis | Statement: [Dyson tree, atmosphereGenerationMethod, photosynthesis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: atmosphereGenerationMethod Context triple: [Dyson tree, atmosphereGenerationMethod, photosynthesis]
-
A.
hasGeneralAtmosphere
Indicates that one entity is characterized by or associated with a particular overall mood, tone, or ambient quality provided by another entity.
-
B.
hasAtmosphere
Indicates that an astronomical body possesses a surrounding layer of gases held by its gravity.
-
C.
hasAtmosphericFeature
Indicates that one entity possesses or exhibits a particular feature or characteristic of its atmosphere.
-
D.
capturesAtmosphereOf
Indicates that one entity successfully conveys or reflects the overall mood, tone, or ambiance characteristic of another entity.
-
E.
atmosphereStyle
Indicates the general mood, ambiance, or experiential character associated with a place, event, or environment.
- 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_69bd46477f9081909d242a327d749466 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85ac8e10819088b6a9e02d927044 |
completed | March 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69bd84583dbc819088a03e3afb30178c |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8501d53c81908371bd5195ba5703 |
completed | March 20, 2026, 5:33 p.m. |
Created at: March 20, 2026, 2 p.m.