Triple
T5234768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lincoln Tree |
E118194
|
entity |
| Predicate | hasPhotosyntheticOrganismType |
P37835
|
FINISHED |
| Object | plant |
—
|
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: plant | Statement: [Lincoln Tree, hasPhotosyntheticOrganismType, plant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotosyntheticOrganismType Context triple: [Lincoln Tree, hasPhotosyntheticOrganismType, plant]
-
A.
photosyntheticOrganism
Indicates that an organism performs photosynthesis, converting light energy into chemical energy to sustain itself.
-
B.
photosyntheticOrgan
Indicates that an entity is an organ specialized for performing photosynthesis in an organism.
-
C.
photosynthesisType
Indicates the specific kind or category of photosynthesis an organism performs (e.g., C3, C4, CAM).
-
D.
photosyntheticTissue
Indicates that an entity has tissue capable of performing photosynthesis, converting light energy into chemical energy.
-
E.
organismType
chosen
Indicates the biological classification or kind of organism that an entity is.
- 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_69bd4467db0881909b3b0982df32cc8f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b064b6881909f5746f55aa422c6 |
completed | March 20, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69bd77bf1ef08190bb3487b3f3ee088c |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:49 p.m.