Triple
T30844456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donatiaceae |
E785596
|
entity |
| Predicate | hasWoodyTissues |
P120646
|
FINISHED |
| Object | lignified tissues present |
—
|
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: lignified tissues present | Statement: [Donatiaceae, hasWoodyTissues, lignified tissues present]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWoodyTissues Context triple: [Donatiaceae, hasWoodyTissues, lignified tissues present]
-
A.
isWoodyPlant
Indicates that the subject is a plant characterized by persistent, woody stems or trunks that remain above ground year-round.
-
B.
isNonWoody
Indicates that an entity lacks woody tissue or characteristics, typically being herbaceous or soft-stemmed rather than woody.
-
C.
hasVascularTissue
Indicates that an entity possesses specialized vascular tissues (such as xylem and phloem) for internal transport of fluids and nutrients.
-
D.
hasXylem
Indicates that an entity possesses xylem tissue or structures for conducting water and nutrients.
-
E.
hasWood
chosen
Indicates that one entity possesses, contains, or is made of wood in relation to another entity 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_69f224b850848190a4af4ccf8ddadcdf |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: April 29, 2026, 8:46 p.m.