Triple
T36599906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peyer’s patches |
E902888
|
entity |
| Predicate | hasEpitheliumType |
P185923
|
FINISHED |
| Object | specialized follicle-associated epithelium lacking typical villi |
—
|
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: specialized follicle-associated epithelium lacking typical villi | Statement: [Peyer’s patches, hasEpitheliumType, specialized follicle-associated epithelium lacking typical villi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEpitheliumType Context triple: [Peyer’s patches, hasEpitheliumType, specialized follicle-associated epithelium lacking typical villi]
-
A.
epitheliumType
chosen
Indicates the specific type or classification of epithelium associated with an entity.
-
B.
polypType
Indicates the specific morphological or histological classification assigned to a polyp.
-
C.
cellType
Indicates the classification relationship that specifies what type of cell an entity is or is associated with.
-
D.
cuticleType
Indicates the type or characteristics of the cuticle associated with an entity.
-
E.
typicalPolypType
Indicates that one entity is the characteristic or most commonly occurring type of polyp associated with the other entity.
- 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_69f76e66b7b88190848f7a3e1188915f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.