Triple
T16991371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tilio-Acerion ravine forests |
E412200
|
entity |
| Predicate | typicalLichenComponent |
P56257
|
FINISHED |
| Object | shade-tolerant epiphytic lichens |
—
|
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: shade-tolerant epiphytic lichens | Statement: [Tilio-Acerion ravine forests, typicalLichenComponent, shade-tolerant epiphytic lichens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLichenComponent Context triple: [Tilio-Acerion ravine forests, typicalLichenComponent, shade-tolerant epiphytic lichens]
-
A.
typicalComponent
chosen
Indicates that one entity is a standard or representative component or part of another entity.
-
B.
typicalLesionLobe
Indicates the brain lobe in which a particular lesion type most commonly or characteristically occurs.
-
C.
componentType
Indicates that one entity specifies or classifies the kind or category of component that another entity represents or uses.
-
D.
component1
Indicates that one entity functions as a constituent or part of another entity within a larger whole.
-
E.
componentRepresents
Indicates that one component stands in for, symbolizes, or models another entity or concept within a system or context.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d280e3348190a27bd5dc7cf87c0e |
completed | April 18, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.