Triple
T10291812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | P-glycoprotein |
E241382
|
entity |
| Predicate | foundInTissue |
P92779
|
FINISHED |
| Object | intestinal epithelium |
—
|
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: intestinal epithelium | Statement: [P-glycoprotein, foundInTissue, intestinal epithelium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foundInTissue Context triple: [P-glycoprotein, foundInTissue, intestinal epithelium]
-
A.
tissueExpression
chosen
Indicates the association between a biological entity (such as a gene or protein) and the specific tissue(s) in which it is expressed.
-
B.
hasTissue
Indicates that one entity possesses, contains, or is associated with a specific tissue of another entity.
-
C.
foundInStructure
Indicates that an entity is located within, contained by, or structurally part of another entity or structure.
-
D.
infectsTissue
Indicates that one entity (typically a pathogen or agent) invades and establishes itself within the tissue of another entity.
-
E.
foundInVolume
Indicates that one entity is physically or logically contained within, or occurs in, a specific volume (such as a book volume, data volume, or bounded collection).
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f117708190928f92ae2611d724 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:42 a.m.