Triple
T1762427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utricularia |
E38685
|
entity |
| Predicate | trapMorphology |
P31462
|
FINISHED |
| Object | bladder-like structures |
—
|
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: bladder-like structures | Statement: [Utricularia, trapMorphology, bladder-like structures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trapMorphology Context triple: [Utricularia, trapMorphology, bladder-like structures]
-
A.
limbMorphology
Indicates the structural form, shape, and configuration of an organism’s limbs in relation to its body.
-
B.
modifiesMorphologyOf
Indicates that one entity alters or changes the morphological structure or form of another entity.
-
C.
morphologicalRelation
Indicates a relationship between linguistic forms where one word or morpheme is derived from, inflected from, or otherwise morphologically related to another.
-
D.
abductionMotif
Indicates a relationship where an event, narrative, or depiction involves the motif of one entity abducting or forcibly carrying off another.
-
E.
tractionType
Indicates the type or method of traction applied or used in relation to an entity or system.
- 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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab173936b4819097332ee185996bbd |
completed | March 6, 2026, 6:04 p.m. |
| PD | Predicate disambiguation | batch_69aa61c9e06c819085489e00cfe72153 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab173830a481908b67928f16f5d999 |
completed | March 6, 2026, 6:04 p.m. |
Created at: March 4, 2026, 7:31 p.m.