Triple
T37449866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shigella |
E930645
|
entity |
| Predicate | invasionTargetCell |
P6647
|
FINISHED |
| Object | intestinal epithelial cells |
—
|
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 epithelial cells | Statement: [Shigella, invasionTargetCell, intestinal epithelial cells]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: invasionTargetCell Context triple: [Shigella, invasionTargetCell, intestinal epithelial cells]
-
A.
targetCellEntryReceptor
Indicates that a receptor mediates or enables the entry of a target cell (or agent) into another cell.
-
B.
invadesFrom
Indicates that one entity initiates an invasion or aggressive incursion into another entity starting from a specified origin or source location.
-
C.
cellInteractionType
Indicates the specific kind of interaction or relationship occurring between cells, such as communication, adhesion, or signaling.
-
D.
infiltrationTarget
Indicates that an entity is the intended object, location, or system that another entity plans to secretly enter, penetrate, or gain unauthorized access to.
-
E.
infectsTissue
chosen
Indicates that one entity (typically a pathogen or agent) invades and establishes itself within the tissue of another 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_69f76ec0b9488190b7a4fae632bd1d2f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb92efc5948190a040ba2028bab964 |
completed | May 6, 2026, 7:13 p.m. |
| PD | Predicate disambiguation | batch_69fb8d0b52588190bb29937a43b99b5e |
completed | May 6, 2026, 6:48 p.m. |
Created at: May 3, 2026, 4:17 p.m.