Triple
T17871532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Givlaari |
E446846
|
entity |
| Predicate | hasTargetCellType |
P3601
|
FINISHED |
| Object | hepatocyte |
—
|
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: hepatocyte | Statement: [Givlaari, hasTargetCellType, hepatocyte]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTargetCellType Context triple: [Givlaari, hasTargetCellType, hepatocyte]
-
A.
cellTypeUsed
Indicates that a particular type of cell is employed or utilized in relation to another entity or process.
-
B.
affectsCellType
Indicates that one entity produces an effect or change on a specific type of cell.
-
C.
hasSafetyCellType
Indicates that an entity is associated with a specific type of safety-related cell used for protection or risk mitigation.
-
D.
hasTarget
Indicates that one entity is directed toward, aimed at, or intended to affect another specific entity as its target.
-
E.
cellType
chosen
Indicates the classification relationship that specifies what type of cell an entity is or is associated with.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49aa30ff8819090c51c1d7767e952 |
completed | April 19, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:18 a.m.